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Project Number: 318023
Project acronym: SmartC2Net
Project title: Smart Control of Energy Distribution Grids over Heterogeneous
Communication Networks
Contract type: Collaborative project (STREP)
Deliverable number: D1.1 - version 2
Deliverable title: SmartC2Net Use Cases, Preliminary Architecture and Business
Drivers
Work package: WP1 -Use Cases and Architecture
Due date of deliverable: M22 – September 2014
Actual submission date: 30/09/2014
Start date of project: 01/12/2012
Duration: 36 months
Editor(s): Giovanna Dondossola, Roberta Terruggia (RSE)
Authors: Giovanna Dondossola (RSE), Roberta Terruggia (RSE)
S. Bessler (FTW), J. Grønbæk (FTW), P. Zwickl (FTW), R. Løvenstein
Olsen (AAU), F. Iov (AAU), Ch. Haegerling (TUDO), F. Kurtz (TUDO), D.
Iacono (RT), A. Bovenzi (RT), S. Marzorati (VO), A. Carrapatoso
(EFACEC)
Contributing partners: FTW Forschungszentrum Telekommunikation Wien (FTW), Aalborg
University (AAU), Technische Universität Dortmund / Communications
Networks Institute (TUDO), ResilTech S.R.L. (RT), Ricerca Sul Sistema
Energetico (RSE), Vodafone Omnitel N.V. (VO), Efacec Engenharia e
Sistemas SA (EFACEC)
Dissemination Level of this Deliverable: PU
Public PU
Restricted to other programme participants (including the Commission Services) PP
Restricted to a group specified by the consortium (including the Commission Services) RE
Confidential, only for members of the consortium (including the Commission Services) C0
This project has received funding from the European Union’s Seventh Framework Programme for
research, technological development and demonstration under grant agreement no 318023. Further
information is available at www.SmartC2Net.eu.
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Introductory note:
Following the first review meeting and the comments received, changes within the updated version 2
have been made in the following sections (notwithstanding the correction of a few minor details in
other places):
Section Executive Summary
Section 1 Introduction: from SmartC2Net UC to the overall architecture
Section 2 The Use Cases and their key elements (Intro)
Section 5 UC ICT requirements & success KPI (All subsections)
Section 11 Annex C - Table of Requirements (All subsections)
Section 12 Annex D - Table of KPIs (All subsections)
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Executive Summary
The SmartC2Net project addresses different control scenarios related to the evolution of the
distribution grids. In order to provide a good coverage of the control applications characterizing the
evolution of European smart grids in the next future, the following four use cases are analyzed in
detail:
• Voltage Control in Medium Voltage Grids
• External Generation Site
• Automated Meter Reading and Customer Energy Management Systems
• Electrical Vehicle Charging in Low Voltage Grids.
Starting from the analysis of these use cases a preliminary global high level architecture is derived at
the aim of highlighting the interactions among the respective control components and ICT networks.
An economic analysis of the use case scenarios is performed for getting the specific business drivers
and business requirements of the envisaged smart grid evolution.
Most outcome from the UC analysis and the overall architecture have provided inputs to the
monitoring, communication, control, evaluation and test bed activities undertaken by the other
project work packages.
The requirements and the Key Performance Indicators (KPIs), initially determined from the use case
analysis, will be used along the whole project running for the evaluation of the SmartC2Net
achievements.
This second version of the deliverable addresses the comments coming from the first review in
Brussels.
First of all the motivations for the four use case selection are better highlighted in the introduction
and in the Use Case chapter (Chapter 2).
The Requirements and KPIs definition and analysis have been improved with the quantitative values
and the mapping with related WPs. The aim is to point out which of the Requirements and KPIs are
addressed by the project developments and how they are evaluated.
As a means to highlight the more relevant elements for the project developments, the priority field
of the requirement template is used and a reduced number of requirements and KPIs has been
focused. This work is reflected in Chapter 11 Annex C and Chapter 12 Annex D, that now provide the
list of enhanced requirements and KPIs presented in a more readable way, and in their enriched
analysis reported in Chapter 5.
Given its relevance to the SmartC2Net exploitation plan, the business analysis have been elaborated
further in deliverable D7.2 where the business drivers and benefits have been linked to the use case
KPIs from SmartC2Net.
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Table of Contents
List of Figures ........................................................................................................................................... 7
List of Tables .......................................................................................................................................... 10
Glossary ................................................................................................................................................. 11
1 Introduction: from SmartC2Net UC to the overall architecture ................................................... 13
2 The Use Cases and their key elements .......................................................................................... 15
2.1 Voltage Control in Medium Voltage Grid ............................................... 16
2.2 External Generation Site ........................................................................ 17
2.3 Automated Meter Reading (AMR) and Customer Energy Management
Systems (CEMS) 19
2.4 Electrical Vehicle Charging in Low Voltage Grids ................................... 21
3 The business drivers ...................................................................................................................... 24
3.1 Business Drivers ..................................................................................... 24
3.1.1 Telco Sector ............................................................................................ 24
3.1.2 Categories .............................................................................................. 27
3.1.3 Use cases ................................................................................................ 32
3.2 Business Requirements .......................................................................... 38
3.2.1 Telco and energy sector interplay .......................................................... 39
3.2.2 Template ................................................................................................ 39
3.2.3 Use cases ................................................................................................ 43
4 UC details ....................................................................................................................................... 49
4.1 Voltage Control in Medium Voltage Grid ............................................... 49
4.1.1 Objective ................................................................................................ 49
4.1.2 Architecture and Sequence Diagrams .................................................... 51
4.1.3 Fault/threat analysis/scenarios .............................................................. 53
4.2 External generation site ......................................................................... 56
4.2.1 Objective ................................................................................................ 56
4.2.2 Control of assets .................................................................................... 59
4.2.3 Network adaptive data transport (AN/WAN) ........................................ 59
4.2.4 Architecture and Sequence Diagrams .................................................... 60
4.3 Automated Meter Reading (AMR) and Customer Energy Management
Systems (CEMS) 63
4.3.1 Objective ................................................................................................ 63
4.3.2 Architecture and Sequence Diagrams .................................................... 64
4.3.3 Fault/threat analysis/scenarios .............................................................. 67
4.4 Electrical Vehicle Charging in Low Voltage Grids ................................... 70
4.4.1 Objective ................................................................................................ 70
4.4.2 Architecture and Sequence Diagrams .................................................... 70
4.4.3 Fault/threat analysis/scenarios .............................................................. 77
5 UC ICT requirements & success KPI ............................................................................................... 78
5.1 Requirement Template .......................................................................... 78
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5.2 Requirements ......................................................................................... 80
5.3 KPIs Template ......................................................................................... 84
5.4 Key Performance Indicators (KPIs) ......................................................... 85
6 Preliminary overall architecture .................................................................................................... 88
6.1 Global architecture ................................................................................ 89
6.1.1 Layered architecture .............................................................................. 89
6.1.2 Distribution of functions ........................................................................ 90
6.2 Use Case mapping .................................................................................. 91
7 Conclusions and Outlook ............................................................................................................... 95
8 Bibliography ................................................................................................................................... 96
9 Annex A - Value Networks ............................................................................................................. 98
9.1 Electrical Grid Value Network ................................................................ 98
9.1.1 Entities ................................................................................................. 100
9.1.2 Main Value Flows ................................................................................. 101
9.2 SmartC2Net Value Network ................................................................. 102
9.2.1 Entities (Revised) .................................................................................. 104
9.2.2 Main Value Flows (Revised) ................................................................. 107
10 Annex B - UC templates ....................................................................... 109
10.1 USE CASE NAME: Medium Voltage Control ......................................... 109
10.1.1 Description of the Use Case ................................................................. 109
10.1.2 Diagrams of Use Case ........................................................................... 112
10.1.3 Technical Details .................................................................................. 120
10.1.4 Step by Step Analysis of Use Case ........................................................ 125
10.1.5 Information Exchanged ........................................................................ 133
10.1.6 Common Terms and Definitions .......................................................... 134
10.2 USE CASE NAME: Electrical Vehicle Charging in Low Voltage Grids .... 135
10.2.1 Description of the Use Case ................................................................. 135
10.2.2 Diagrams of Use Case ........................................................................... 138
10.2.3 Technical Details .................................................................................. 148
10.2.4 Step by Step Analysis of Use Case ........................................................ 153
10.2.5 Information Exchanged ........................................................................ 159
10.2.6 Common Terms and Definitions .......................................................... 159
10.3 USE CASE NAME: External generation site .......................................... 160
10.3.1 Description of the Use Case ................................................................. 160
10.3.2 Diagrams of Use Case ........................................................................... 163
10.3.3 Technical Details .................................................................................. 168
10.3.4 Step by Step Analysis of Use Case ........................................................ 172
10.3.5 Information Exchanged ........................................................................ 176
10.3.6 Common Terms and Definitions .......................................................... 177
10.4 USE CASE NAME: Automated Meter Reading (AMR) and Customer
Energy Management Systems (CEMS) ............................................................................................ 178
10.4.1 Description of the Use Case ................................................................. 178
10.4.2 Diagrams of Use Case ........................................................................... 186
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10.4.3 Technical Details .................................................................................. 198
10.4.4 Step by Step Analysis of Use Case ........................................................ 202
10.4.5 Information Exchanged ........................................................................ 215
10.4.6 Common Terms and Definitions .......................................................... 215
11 Annex C - Table of Requirements ......................................................... 217
11.1 Requirements for Medium Voltage Control Use Case ......................... 217
11.2 Requirements for EV Charging Use Case ............................................. 223
11.3 Requirements for External Generation Use Case ................................ 226
11.4 Requirements for AMR and CEMS Use Case ........................................ 231
12 Annex D - Table of KPIs ........................................................................ 237
12.1 Key Performance Indicators for Medium Voltage Control Use Case ... 237
12.2 Key Performance Indicators for EV charging Use Case ........................ 240
12.3 Key Performance Indicators for External Generation Use Case .......... 242
12.4 Key Performance Indicators for AMR and CEMS Use Case .................. 243
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List of Figures
Figure 1 Overview of Medium Voltage Control Use Case ..................................................................... 16
Figure 2 Overview of External Generation Site Use Case ..................................................................... 18
Figure 3: Advanced Smart Meter Reading and Customer Energy Management System Scenario ....... 20
Figure 4 Overview of the EV Use Case .................................................................................................. 23
Figure 5 M2M device connections, energy and utility sector, worldwide, 2011–2021 [ANME12] ...... 25
Figure 6 – A categorisation of generic business drivers ........................................................................ 28
Figure 7 – A categorisation of business requirements .......................................................................... 39
Figure 8 - The Medium Voltage Control Function ................................................................................. 50
Figure 9 The UC Architecture ................................................................................................................ 51
Figure 10 Voltage Control – Communications ...................................................................................... 52
Figure 11 Medium Voltage Control Sequence Diagram ....................................................................... 53
Figure 12 Possible attack scenarios to the Voltage Control function ................................................... 54
Figure 13 Estimated RES Power per Substation (2020) ......................................................................... 55
Figure 14: Overview of external generation site use case .................................................................... 57
Figure 15: Overview of use cases – and fault/error cases. ................................................................... 58
Figure 16 Components distributed in the external grid operation case ............................................... 60
Figure 17 Functionalities in the external grid operation case ............................................................... 61
Figure 18 Overview of the sequence diagram for normal operation mode, capturing Control of Assets
and Data Transport. The specific fault/error cases can be seen in Annex B. ....................................... 62
Figure 19 Physical components of the use case and their locations in the Smart Grid setup .............. 64
Figure 20 Detailed use case clustering structure .................................................................................. 65
Figure 21 Mis-use diagrams for the considered CEMS functionalities.................................................. 67
Figure 22: Mis-sequence diagram for the MIM attack .......................................................................... 69
Figure 23 Networks of the EV use case ................................................................................................. 72
Figure 24 Overview of the interactions between components ............................................................ 73
Figure 37 Requirements: Project WP mapping ..................................................................................... 80
Figure 38 Requirements: WP2, WP3 and WP4 mapping Figure 39 Requirements: WP5 and WP6
mapping ................................................................................................................................................. 81
Figure 25 Requirements: Use Case ........................................................................................................ 81
Figure 26 Requirements: Category ........................................................................................................ 82
Figure 27 Requirements: Level .............................................................................................................. 82
Figure 28 Requirements: Priority .......................................................................................................... 82
Figure 29 MVC UC Requirements: Category Figure 30 MVC UC Requirements: Level ........... 83
Figure 31 EV UC Requirements: Category Figure 32 EV UC Requirements: Level ........... 83
Figure 33 EGS UC Requirements: Category Figure 34 EGS UC Requirements: Level .......... 83
Figure 35 CEMS AMR UC Requirements: Category Figure 36 CEMS AMR UC Requirements: Level . 84
Figure 40 KPIs: Project WP mapping ..................................................................................................... 85
Figure 41 WP2, WP3 and WP4 mapping Figure 42 WP5 and WP6 mapping.......... 86
Figure 43 KPIs: Use Case ........................................................................................................................ 86
Figure 44 KPIs: Scope ............................................................................................................................ 87
Figure 45 KPIs: Category ........................................................................................................................ 87
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Figure 46 MVC UC KPIs: Category Figure 47 MVC UC KPIs: Scope ...................... 87
Figure 48 EV UC KPIs: Scope Figure 49 EV UC KPIs: Category ..................... 88
Figure 50 EGS UC KPIs: Scope Figure 51 EGS UC KPIs: Category ............. 88
Figure 52 CEMS AMR UC KPIs: Scope Figure 53 CEMS AMR UC KPIs: Category ... 88
Figure 54 Overview of the SG architecture ........................................................................................... 90
Figure 55 Overview of Use Cases mapping ........................................................................................... 92
Figure 56 Detailed view of Use Cases mapping..................................................................................... 93
Figure 57: “Classical” Electrical Grid Value Network ............................................................................. 99
Figure 58 – SmartC2Net Value Network (with special consideration of chosen use cases) ............... 103
Figure 59 - Voltage Control ................................................................................................................. 113
Figure 60 - Voltage Control - Actors Interactions ................................................................................ 113
Figure 61 - Voltage Control - Use Case Diagram ................................................................................. 114
Figure 62 - Voltage Control - Use Case Diagram - attack scenarios .................................................... 114
Figure 63 - Voltage Control – Mapping on SGAM ............................................................................... 115
Figure 64 - Voltage Control - Overview of involved communications ................................................ 115
Figure 65 – Voltage Control – Communications .................................................................................. 116
Figure 66 – Voltage Control - Component Layer ................................................................................. 116
Figure 67 - Generation Forecast .......................................................................................................... 117
Figure 68 - Generation Forecast - Sequence Diagram ........................................................................ 117
Figure 69 – Voltage Control - Sequence Diagram ............................................................................... 118
Figure 70 - Voltage Control - DoS Attack to DER ................................................................................. 118
Figure 71 - Voltage Control - DoS Attack to MVGC ............................................................................. 119
Figure 72 - Voltage Control - Fake DER Set point ................................................................................ 119
Figure 73 - Voltage Control - Fake DER Set point (Man in the Middle) ............................................... 120
Figure 74 - Voltage Control - Fake TSO signal ..................................................................................... 120
Figure 75 Use case components and Networking Connectivity Options ............................................ 139
Figure 76 - Use Case Diagram for EV charging scenario ...................................................................... 140
Figure 77 - Message Sequence Diagram for EV charging scenario ..................................................... 141
Figure 78 - Use Case Diagram for energy and power management scenario ..................................... 142
Figure 79 - Message Sequence Diagram for energy and power management scenario .................... 143
Figure 80 - Use Case Diagram for Energy Market scenario ................................................................. 144
Figure 81 - Message Sequence Diagram for Energy Market Scenario ................................................ 145
Figure 82 - SGAM Function Layer ........................................................................................................ 146
Figure 83 – AS3 Metering information interrupted ............................................................................ 146
Figure 84 – AS2 LVGC-CSO connection interrupted ............................................................................ 147
Figure 85: Diagram of the Interactions described in section 4.1 ........................................................ 148
Figure 86 Overview of Use Case .......................................................................................................... 162
Figure 87 Overview of use cases ......................................................................................................... 164
Figure 88 Set of physical components and their locations in the smart grid setup ............................ 165
Figure 89 Different communication means used for the various components to interact with each
other .................................................................................................................................................... 166
Figure 90 Different functionalities used in the system in order to be able to execute the use cases
over the network on the different physical components ................................................................... 167
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Figure 91: Advanced Smart Meter Reading and Customer Energy Management System Scenario ... 186
Figure 92: Physical components of the use case and their locations in the Smart Grid setup ........... 187
Figure 93: Detailed use case clustering structure ............................................................................... 188
Figure 94: MM.01 Obtain meter reading on demand (refer to [4]) .................................................... 189
Figure 95: Sequence diagram MM.01.01 - Obtain remote meter reading on demand (refer to [4]) . 189
Figure 96: Sequence diagram MM.01.02 - Obtain walk-by meter reading on demand (refer to [4]) 190
Figure 97: MM.02 Obtain scheduled meter reading (refer to [5]) ...................................................... 190
Figure 98: Sequence diagram MM.02.01 - Obtain scheduled meter reading (refer to [5]) ................ 190
Figure 99: Sequence diagram MM.02.02 - Configure reading schedule (refer to [5]) ........................ 191
Figure 100: MM.03 Set tariff parameters (refer to [6]) ...................................................................... 191
Figure 101: Sequence diagram MM.03.01 - Set tariff parameter in the smart meter (refer to [6]) ... 191
Figure 102: Sequence diagram MM.03.02 - Set tariff parameter in the LNAP/NNAP(refer to [6]) .... 192
Figure 103: CI.01. customer information provision (refer to [8]) ....................................................... 192
Figure 104: Sequence diagram CI.01.01 - Send information to meter display (refer to [8]) .............. 193
Figure 105: Sequence diagram CI.01.02 - Send information to simple external consumer display (refer
to [8]) ................................................................................................................................................... 193
Figure 106: Sequence diagram CI.01.03 -– Smart Meter publishes information on simple external
consumer display (refer to [8]) ............................................................................................................ 193
Figure 107: ES.02 - Manage supply quality (refer to [7]) .................................................................... 194
Figure 108: Sequence diagram ES.02.01 - Configure power quality parameters to be monitored (ref.
[7]) ....................................................................................................................................................... 194
Figure 109: Sequence diagram ES.02.02 - Smart meter sends information on power quality to display
(refer to [7]) ......................................................................................................................................... 194
Figure 110: DG.01.01 - Direct load / generation demand – appliance has end-decision about its load
adjustment (refer to [14]) ................................................................................................................... 195
Figure 111: DG.01.02 - Direct load / generation demand - appliance has no control over its own load
adjustment (refer to [14]) ................................................................................................................... 196
Figure 112: Sequence diagram DG.03.01 - Information regarding power consumption / generation of
individual appliances (refer to [16]) .................................................................................................... 196
Figure 113: Sequence diagram DG.03.02 - Information regarding total power consumption (refer to
[16]) ..................................................................................................................................................... 197
Figure 114: Sequence diagram DG.03.03 - Price & environmental information (refer to [16]) ......... 197
Figure 115: Sequence diagram DG.03.04 - Warning signals based individual appliances consumption
(refer to [16]) ....................................................................................................................................... 197
Figure 116: External Actors (refer to [1]) ............................................................................................ 198
Figure 117:Mis-use diagrams for the considered CEMS functionalities ............................................. 208
Figure 118 Mis-sequence diagram for the MIM attack ....................................................................... 210
Figure 119: Mis-sequence diagram for the Masquerade attack ......................................................... 212
Figure 120 Mis-sequence diagram for the DoS attack ........................................................................ 213
Figure 121: Mis-sequence diagram for the Disclosure of message attack.......................................... 214
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List of Tables
Table 1 Overview of the CEN-CENELEC-ETSI AMR / CEMS sequence diagrams of Annex B - UC
templates............................................................................................................................................... 66
Table 2: Overview of the mis- sequence diagrams of Annex B - UC templates .................................... 70
Table 3 Requirements Template Description ........................................................................................ 79
Table 4 KPIs Template Description ........................................................................................................ 84
Table 5 Requirements for Medium Voltage Control Use Case ........................................................... 223
Table 6 Requirements for EV Charging Use Case ................................................................................ 226
Table 7 Requirements for External Generation Use Case ................................................................... 231
Table 8 Requirements of the AMR / CEMS Use Case .......................................................................... 236
Table 9 Key Performance Indicators for Medium Voltage Control Use Case ..................................... 240
Table 10 Key Performance Indicators for EV charging Use Case ........................................................ 241
Table 11 Key Performance Indicators for External Generation Use Case ........................................... 242
Table 12 Key Performance Indicators of the AMR / CEMS Use Case .................................................. 244
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Glossary
Acronym Definition
AC Air Conditioning Unit
AMI Advanced Monitoring Infrastructure
AMR Automated Meter Reading
AVR Automatic Voltage Regulator
CAM Control Area Manager
CEMS Customer Energy Management System
CHP Combined Heat and Power
CI Customer Information
CLS Controllable Load System
CPE Customer Premises Equipment
CS Charging Spot
CSO Charging Station Operator
CSP Connectivity Service Provider
DER Distributed Energy Resource
DG Distributed Generation
DMS Distribution Management System
DNO Distribution Network Operator
DoS Denial of Service
DSM Demand Side Management
DSO Distribution System Operator
EMG Energy Management Gateway
ESP Energy Service Provider
EV Electric Vehicle
FLIR Fault Location, Isolation and Restoration
GIS Geographic Information System
HAN Home Area Network
HES Head End System
HV High Voltage
IP Internet Protocol
KPI Key Performance Indicator
LAN Local Area Network
LNAP Local Network Access Point
LV Low Voltage
LVGC Low Voltage Grid Controller
M2M Machine-to-Machine
MDA Metering Data Aggregator
MDMS Meter Data Management System
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MIM Man In the Middle
MO Meter Operator
MPLS Multiprotocol Label Switching
MV Medium Voltage
MVGC Medium Voltage Grid Controller
MVNO Mobile Virtual Network Operator
NAN Neighbourhood Area Network
NNAP Neighbourhood Network Access Point
OLTC On Load Tap Changer
OMS Outage Management System
P Active power
PEV Plug-in Electric Vehicle
PG Power Grid
Q Reactive power
RES Renewable Energy Sources
SAS Substation Automation System
SGAM Smart Grid Architecture Model
SM Smart Metering
SSM Supply Side Management
TSO Transmission System Operator
UC Use Case
UI User Interface
V Voltage
VC Voltage Control
VPP Virtual Power Plant
WAN Wide Area Network
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1 Introduction: from SmartC2Net UC to the overall architecture
The expected growth in Distributed Generation (DG) will significantly affect the operation and the
control of today’s distribution systems. Being confronted with short time power variations of DGs,
the assurance of a reliable service (grid stability, avoidance of energy losses) and the quality of the
power may become costly. In this light, Smart Grids may provide an answer towards a more active
and efficient electrical network.
The SmartC2Net project addresses different control scenarios related to the evolution of the
European distribution grids. In particular this deliverable addresses the WP1 activity consisting in the
description of selected use cases with the identification of the requirements and details needed by
the others WPs. A first sketch of the overall architecture is presented and the specific economical
business driver derived.
Decision criteria for the selection of the use-cases are the following:
(1) architectural coverage of the smart grid domains and control layers;
(2) coverage of the time horizon from use-cases that are about to be implemented until future
smart grid control scenarios with deployment in 5-10 years;
(3) relevance/contribution to efficient LV/MV grid operation;
(4) challenges of the use-cases with respect to communication load, communication network
performance and control robustness.
Following the guidelines on the harmonized specification of smart grid use cases provided by the
committee Sustainable Processes of the Smart Grid Coordination Group by CEN/CENELEC/ETSI [UCC],
the following four use cases are analyzed:
Voltage Control in Medium Voltage Grids
External Generation Site
Automated Meter Reading (AMR) and Customer Energy Management Systems (CEMS).
Electrical Vehicle Charging in Low Voltage Grids.
Addressing different actors and control layers of the distribution grid, these use-cases provide a good
coverage of the applications characterizing the evolution of European smart grid in the next future:
from the medium voltage grids of the “Voltage Control in Medium Voltage Grid” use case, towards
the low voltage grids and customers involved in “Automated Meter Reading (AMR) and Customer
Energy Management Systems (CEMS)” use case. Some use cases, as Voltage Control in Medium
Voltage Grids and Automated Meter Reading (AMR) and Customer Energy Management Systems
(CEMS) deepen the ICT aspects starting from UC descriptions taken from CEN/CENELEC/ETSI
Coordination Groups on Smart Grid and Smart Meter, respectively. Others, as Electrical Vehicle
Charging in Low Voltage Grids and External Generation Site, are fully new control cases. In all cases
the goal of the analysis is to provide detailed views of the information, communication and
component layers of their control architectures.
Starting from the analysis of these use cases a preliminary global high level architecture is derived at
the aim of highlighting the interactions among the respective control components and ICT networks.
As planned in the project Annex I [DoW] in the next phase of the Task 1.2 this preliminary
architecture will be updated and integrated with the results obtained from the monitoring (WP2),
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communication (WP3) and control (WP4) architecture developments, and a more detailed version of
the SmartC2Net overall architecture will be provided in D1.2.
An economic analysis of the use case scenarios is performed for getting the specific business drivers
and business requirements of the envisaged smart grid evolution. More updated analysis of business
drivers and business requirements will be presented in Deliverable D.7.2.
The requirements and the Key Performance Indicator (KPI) for the evaluation of the SmartC2Net
achievements are determined from the use case analysis and they are studied under several
perspective in order to identify the most important ones. The mapping with the different
SmartC2Net WPs allows understanding how the project results will be addressed and evaluated.
In order to increase the readability of the document, the deliverable is organized into core chapters
presenting the basic methods and most relevant aspects, and a set of annexes providing further
details.
The core part is structured into seven chapters, as follows: chapter 2 introduces the key elements of
the four use cases, then chapter 3 presents the business drivers and the business requirements
related to the use cases. More details regarding the use cases are described in chapter 4 where the
fault/threat scenarios are introduced, and an extended requirement and KPI analysis is presented in
chapter 5. Chapter 6 presents a first high level sketch of the SmartC2Net architecture. Finally,
chapter 7 concludes the deliverable.
Annex A presents the SmartC2Net Value Network used for the analysis of the business drivers; Annex
B includes the full templates of the four UCs by adopting the standard template proposed by IEC TC8
AHG 4 [IEC TC8], Annexes C and D include the refined UC requirements and KPIs lists, respectively.
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2 The Use Cases and their key elements
This Chapter introduces a general vision of the four Use Cases that will be described with more
details in Chapter 4. Following the guidelines on the harmonized specification of smart grid use cases
provided by the committee Sustainable Processes of the Smart Grid Coordination Group by
CEN/CENELEC/ETSI [UCC], the following four use cases are analyzed:
Voltage Control in Medium Voltage Grid
External Generation Site
Automated Meter Reading (AMR) and Customer Energy Management Systems (CEMS)
Electrical Vehicle Charging in Low Voltage Grids.
The selected Use Cases provide a good coverage of the applications characterizing the evolution of
European smart grid in the next future and address the major actors and control layers of the power
grid.
In particular the Voltage Control in Medium Voltage Grids use case addresses a key functionality in
the operation of DER connecting grids, and considers the ICT aspects and related cyber security
challenges. The connection of DERs to medium voltage grids can perturb the status of the whole
power grid: the non-deterministic behavior of DERs should be managed using ICT components in
order to avoid effects on the contracted terms of the DSO (Distribution System Operator) with the
TSO (Transmission System Operator) and on the quality of service of the neighbor grids.
The external generation site resembles a small town with some local industry, covering both low
voltage and medium voltage quality control. The scenario setup is a quite typical setup in many
places in Europe and therefore has a significant relevance.
The Automated Meter Reading (AMR) and Customer Energy Management Systems (CEMS) describes
two basic functionalities for enabling future distribution grids for load balancing and integration of
decentralized and distributed (renewable) energy resources. Different European utilities are moving
on the introduction of these functionalities on their grids. According to the European Mandate
M/441, a monthly billing for the customer and a roll-out of smart meters in 80% of all European
households until 2020 is targeted, which requires cost-efficient, modular concepts for the
comprehensive deployment of smart metering devices enabling a variety of flexibility management
scenarios. New customer programs to make the home power consumptions more “intelligent” are
emerging.
A specific flexibility management use case is represented by the Electrical Vehicle Charging in Low
Voltage Grids. In order to reach the European 2020 climate and energy package, in particular the 20%
reduction of CO2, new energy strategies are evaluated. The transition from fuel-powered cars to
Electrical Vehicles represents a challenging goal that need to be addressed by the power utilities in
order to avoid problems on the electrical grid due to the recharging operation and to make this
transition attractive for customers.
The functionalities addressed by the selected use cases represent interesting and relevant aspects for
the External Advisory Board members composed by DSO from different countries. The discussion and
the iteration performed during the first meeting and continuing in the next ones allow obtaining an
aligned vision with the real needs of the utilities for the future European distribution grids.
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The focus of the analysis is given to the ICT aspects and to the communication needs of the control
scenarios. Both normal and abnormal behaviors are addressed by each Use Case, describing the
effect of malicious attacks or accidental faults. The interactions among the Use Cases, participating to
the control of the whole grid system, are shown in Chapter 6.
2.1 Voltage Control in Medium Voltage Grid
The primary aim of this use case is to address the communication needs of a Voltage Control function
for medium voltage grids connecting Distributed Energy Resources (DERs). The actions derived from
the Voltage Control function are considered with the specific aim of defining an ICT architecture
suitable for the security analysis. The Medium Voltage Control is a didactic case for illustrating the
need of cyber security in smart grid applications, first because its behaviour influences both the
system operation and economy, secondly for the high level of inter-networking of its ICT
architecture. The evaluation of attack processes to the Voltage Control function is aimed at
identifying security controls to counter act those attacks having the capability of compromising the
voltage profile [DGPT12].
The connection of DERs to medium voltage grids can influence the status of the whole power grid:
the behaviour of DERs can affects the capacity of the DSO (Distribution System Operator) to comply
with the contracted terms with the TSO (Transmission System Operator) and directly the quality of
service of their neighbour grids.
The main functionality of the medium voltage control function is to monitor the active distribution
grid status from field measurements and to compute optimized set points for DERs, flexible loads and
power equipment deployed in HV/MV substations.
Figure 1 Overview of Medium Voltage Control Use Case
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The optimization function is performed by a Medium Voltage Controller of a HV/MV substation
control network. In order to pursue the previously defined objective, the Controller calculates in a
coordinated manner the optimal states of the controllable devices across the substation area.
The control strategy requires information originating externally to the DSO domain. From the
operation stand point, the optimization function has to receive voltage regulation requests by the
TSO whenever a transmission grid contingency needs to apply preventive measure to voltage
collapse. Load and generation forecasts are used to optimize the operation of distributed devices,
while the economic optimization is based on market prices and DER operation costs.
A first major design assumption underlying the use case ICT architecture (see Chapter 6) is that
communications from the DMS (Distribution Management System) application in the DSO centre
provide to the Controller the information related to DER features, changes in the grid topology,
requests by TSO, load/generation forecasts and market data. This design choice preserves the
integrity of the distribution grid operation by limiting the communication channels at the substation
level and concentrating the communications with those external actors at the DSO centre level.
The control loop is triggered by critical events (e.g. under/over voltage event, TSO request, grid
topology change). In absence of criticalities, the VC function is executed on a periodic base (e.g.
every 15 minutes) for optimization purposes. The total response time of its closed control loop, from
the start of the elaboration to the end of the set point actuation, depends on actuation time
constants of OLTC and DER power electronics.
The architectural layout deployed for implementing the VC function depends on the responsibilities
attributed to the use case roles and on country-based regulations. According to the architectural
layout in Figure 1, the data supply chain of the VC function depends on several communication links
enabling remote accesses from systems outside the perimeter of the DSO operation. The DMS
application in the DSO centre has permanent links (the green WAN in Figure 1) with four actors (TSO,
Aggregator, Generation Forecaster and Load Forecast); the Controller in the DSO substation has
permanent communication links (the red WAN in Figure 1) with third party DERs, possibly deploying
heterogeneous communication technologies available in different geographical areas;
communications between DMS and substation automation and control systems pass through the
DSO SCADA links (the blue WAN), possibly based on telco services. By focusing on the core of the VC
scheme, it results evident that the correct elaboration of the optimal set points depends on the
provision of correct operation and economic data from the above communication channels. A
malicious attack to one of the above communication links may cause either the loss of input data
(generation forecasts, economic data from the Aggregator, TSO requests, topological changes), or
the introduction of faked input values or output set points. The effects of such communication
attacks may lead the control function either to diverge from optimum set points or, even worst, to
produce inadequate set points with cascading effects on connected generators. The global impact of
cyber attacks to the Voltage Control functions on the supplied power depends on the grid size, the
amount of distributed generation, the control network topology on the top of the power grid
structure and the extension of the attack.
2.2 External Generation Site
With the anticipated increase in small decentralized energy resources from primary wind and
photovoltaic (PV), the low voltage (LV) grids are exposed to new load scenarios than originally
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designed for. Further, new high consumer demands from Electrical Vehicle (EV) mobility and heat
pumps challenge existing LV grid infrastructures additionally. As a result, there is an increased
interest in technologies to improve the LV grid operation. These mainly entail: local energy storage,
active control of energy fed in electrical grid, flexible demand control (entailing both end-user
managed demand response and autonomic demand control) for house-holds and EVs. This use case
covers the automation and control techniques required for future LV grids and enables the DSO to
utilize the flexibility of the LV grid assets. All this happens over an imperfect communication network
which poses challenges to the operation of the grid. Therefore, the objective of this use case is to
demonstrate the feasibility of controlling flexible, distributed loads and renewable energy resources
in LV grids over an imperfect communication network. Flexibility of LV grids for upper hierarchical
control levels is also investigated.
Primary Substation
Automation&Control
MVGC
ProsumerLarge DER Large DER
HV Grid
HV
MV
MV
LV
Prosumer
Consumer
Interm. DER
Consumer
MicroDER
SME
Farm
SME
EnergyStorage
…
MV
LV
...
...
...
...
MV
LV
Use Case 2.3
Prosumer
Retailers
DMS
TSO
ForecastProviders
Markets
AggregatorsMV/LV
WAN
AN
Technical Flexibility
&Performance
Commercial Feasibility
& Flexibility
AN Provider(s)
AN Provider(s)
WAN Provider(s)
Secondary Substation
Automation&Control
Secondary Substation
Automation&Control
Secondary SubstationAutomation & Control
LVGC
Figure 2 Overview of External Generation Site Use Case
The reference scenario for this use case consists of a MV and LV grid shown in Figure 2, contains: 1)
fixed and shift-able energy consumption from households, small enterprises and EVs, 2) production
from PVs and wind turbines, 3) Energy storage. Hierarchical controller architecture is utilized, where
a distribution management system (DMS) is at the upper most level. This provides commands to the
MV grid controller, which sends commands to the LV grid controllers as well as flexible generation
and consumption in the MV grid. Finally, the LV grid controller sends commands to flexible assets in
the LV grid. The LV grids are connected to the MV grid via a controllable transformer station with an
online tap changer (OLTC).
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It is considered that all components in the architecture are connected with a communication
network providing monitoring data from and control of the individual components. The LV grid
implements its own control mechanisms which are responsible for: a) maintaining an acceptable
voltage profile, security and safety, b) balancing available power resources (energy storage and
generation) with the (flexible) demand, and c) handling the interactions between a) and b). The
control infrastructure is managed by one or more dedicated LV grid controllers which provide
functionality to support the sub-use cases introduced in the following sections. This Use Case is
considering only faults and performance degradation within the public communication network, and
the system’s overall ability to perform normal grid operation even during network faults and
performance degradation.
With the introduction of significant decentralized energy production from wind and photovoltaic
plants in the LV grid along with energy storage as illustrated in Figure 2, new problems arise. In this
setting the low voltage grid control should preferably be able to: 1) control the voltage profile along
the low voltage feeders, 2) optimize MV grid losses; 3) optimize energy cost; 4) aggregate the
flexibility of LV and MV assets that can be used as an input to the MV control and distribution
management system (DMS). The grid operation should in this matter be resilient to faults and
performance degradation in the public communication lines between the low voltage grid controller
and the assets in the electrical grid with special focus on the low voltage side, hereby limiting the
effect of changing network conditions on the electrical grid performance. This means that the use
case also includes mechanisms for adapting the communication to events in the network that
challenge the communication and the quality of the data exchanged between the controlled and
controlling entities.
Under these settings, two focus points are defined as to show the above characteristics:
- Technical flexibility and performance: Resilience of control towards faults and congestions in
communication networks.
- Commercial feasibility and flexibility: Aggregation of generation and demand (abstraction of
models).
2.3 Automated Meter Reading (AMR) and Customer Energy Management Systems
(CEMS)
This use case describes two basic functionalities for enabling future distribution grids for load
balancing and integration of decentralized and distributed (renewable) energy resources (Figure 3).
Therefore, Automated Meter Reading (AMR) is an enabling technology, which is capable of
generating precise multi-sector metering data and aggregate them on local grid operator side for
large-area and in-house analysis of current energy consumptions as well as grid load conditions.
Additionally, current efforts in the context of the Internet of Things aim to connect more devices in
the household to create a more intelligent home area network (HAN), including components of
customer energy management systems (CEMS) like distributed energy resources (DER) and storages,
demand side management, private electric vehicle charging and user interaction. In the context of
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AMR, this adds an additional way of home building automation by combining the energy
consumption of accordant components with the current status of the energy grid to improve its
stability by shifting loads balanced with the neighborhood area network.
Shiftable
loads
In house applications
Communication
hub
Local CHP
Photovoltaic
Household
appliance
Air
conditioning
units
Decentralized
power production
Smart
Metering
Smart
Metering
EMG
User
interface
Home area network with AMR / CEMS
CommunicationPower
ControlMetering
Energy grid
Communication network
Neighbourhood area
network
Control
Data aggregator
Power predictor
Cellular
networkCellular
network
Fixed
network
To MV grid
Cellular
network
Fixed or cellular
network
Ag
gre
ga
ted
me
teri
ng
da
taWind turbines
Figure 3: Advanced Smart Meter Reading and Customer Energy Management System Scenario
AMR is often referred as the key application for enabling a Smart Grid. Basically, AMR represent
different approaches for automatically collecting energy consumption data from electric, gas, water
and heating metering devices and transmitting these data to the meter reading operator for billing
and accounting. This information enables the energy utilities for an accurate meter reading and a
detailed forecast of the predicted energy consumption. Since several years AMR systems are already
deployed mainly for industrial and commercial customers, based upon an integrative approach by
combing the actual metering components and a WAN interface for remote meter reading. Due to the
European Mandate M/441, a monthly billing for the customer and a roll-out of Smart Meters in 80%
of all European households until 2020 is targeted, which requires cost-efficient, modular concepts for
the comprehensive deployment of Smart Metering devices considering a variety of application
scenarios. Due to different technology life cycles for energy components and ICT components a
modular system is targeted in most of the approaches. Usually a Metering HAN Gateway collects and
stores metering data from several metering devices, like electricity, gas, water and heating meters
connected by short range radio, e.g. ZigBee or Wireless M-Bus. The collected data is bundled and
securely transmitted to the meter reading operator by different access technologies, based on
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wireless, wired or PLC technologies. Moreover, a local feedback system gives the prosumer
transparent insight into his current energy consumption. In conjunction with available tariff
information, motivation for reducing overall power consumption can be achieved.
Additionally to the basic functionality of the AMR deployment, a more balanced usage of volatile
renewable energy sources (RES) and shift-able and controllable load system (CLS) in the distribution
grids is achievable by an active integration of the components on the customer side. In this context,
several customer energy management systems (CEMS) are presented, like locally managed and self-
sustaining Micro Grids, virtual power plants and centralized load coordination like DSM or DER based
on dynamic energy prices. All approaches focus on the bidirectional integration of DER and
prosumers (producers and consumers) from both power and communication engineering's point of
view. This includes volatile RES such as wind farms and photovoltaic systems, as well as energy-aware
households, which are enabled by AMR to get a detailed forecast of the energy demand and
additional transparency in energy consumption on the customer side. Moreover, based on CLS and
DG through Combined Heat and Power (CHP) generation, micro-turbines and intelligent photovoltaic
(PV) panels, the ability to balance load peaks and valleys is given. These approaches require, because
of the distributed installations and small shift-able load potential, an aggregation of multiple DER.
Through concepts such as VPP, microgrids and energy hubs, different components are combined
using various networking concepts into a logical, partly independent group (e.g. isolated networks).
At this point, the seamless integration, reliable and near real-time connectivity within the households
by an Energy Management Gateway (EMG) and a CEMS, which is required for DER and DSM at the
customers side, are key capabilities of reliable power distribution grids.
All in-house components assume to be connected via a CEMS, which can be realized by a dedicated
wired or wireless home automation system (e.g. narrowband PLC, broadband PLC, BUS systems,
ZigBee, W-MBus, etc.) or a shared medium provided by the customers in-house networks (e.g.
wireless LAN, broadband PLC, etc.). At least one access technology (at least cellular networks), but
potentially more communication means, depending on the existing possibilities, e.g. power line, 3G
or fiber (if already installed in the household) and operators, may differ between households. Faults,
of different varieties, that might occur in context of this Use Case are addressed by Chapter 4.3 of
this deliverable.
2.4 Electrical Vehicle Charging in Low Voltage Grids
This use case describes the charging of electrical vehicles in a low voltage grid considering both public
as well as private charging (Figure 4). The overall objectives of the use case are to provide EV
charging service by:
• Satisfying the charging demands of arriving EVs in such a way that the charging load is distributed
according to the resource capacities in time and space (geographical routing for public charging).
• Enabling electrical vehicle to charge flexibly, a feature that can be used by the local DSO to manage
power quality control in the LV grid along with decentralized PV production as well as other loads
(e.g. households), and by the EV aggregator to handle on the energy market.
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• Providing a system architecture that enables interoperation between new actors such as charging
station operator, the EV routing service provider, the EV aggregator, and existing actors such as DSOs
and energy market.
• Enabling the DSOs to monitor the state of low voltage grid under EV load conditions.
The EV charging scenarios described in this document cover the pre-charging scenario (not in detail)
and the smart charging scenario (similar to CG-CG/M490 document, scenario WGSP-1300). The pre-
charging interactions occur before arrival at the charging spot. The interaction of the EV with the
Charging Station Operator (CSO) (mediated by a routing service) leads to a reservation and the
allocation of a charging spot (CS), as well as the communication of desired charging demand, arrival
time, leave time, etc. from the EV to the CSO. The CSO can already create a plan. Also without the
pre-charge phase, the smart charging scenario is possible: the EV arrives at a free CS and requests
the CSO to charge, while providing following data: arrival time (now), estimated departure time,
minimum required amount of energy, maximum required amount of energy (to fill the battery),
preferred charging speed (sub-scenario PS2). The CSO creates a schedule, based on up-to-date
information: a) from the DSO about the charging capacity at that certain grid bus (available power),
b) energy bought optimally on the market, following the offered (flexible) demand.
The use case also considers how the DSO can supervise the Low Voltage grid to observe potential
power quality issues. The tool for the DSO to ensure power quality is a low voltage grid controller at
the secondary sub-station providing the available power limitations and flexibility demands to the
charging services. The low voltage grid controller utilizes the flexibility in conjunction with local
power resources (battery and production) to actively control power quality.
A regional EV aggregator (or energy supplier) interacts with the market (retail and spot) and buys the
EV charging energy according to the demand predicted by the charging stations. This demand is
expressed specifying also the flexibility of the consumption, for which the charging station is
rewarded. The aggregated requested EV demand cannot exceed the LV grid capacity (expressed by
the available power).
Specific for SmartC2Net are the following communication failure sub-scenarios: in the first the
communication channel from DSO to CSO for updating the available power is interrupted, implying a
reduction of the charging duration or the intensity of all current operations, and in latter the
metering data flow used for estimating the available power from the consumption and generation
forecasts is disrupted. Due to this uncertainty, the calculated available power could be reduced for
safe operation.
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Charging Spot
Charging station
Operator(Controller)
Charging stationRouting
Meter
LVGrid Controller
EVAggregator
LVNetwork
internet
Control
MeterAggregation
Market
MeterNetwork
MVGridController
Load
prediction
Available
power
Network
Sell
Flexibilitybuy energy
reservations
availability
buy energy
query & reserve
plugin/ leave
BatteryPV
Inverter
Meter Meter
control
Figure 4 Overview of the EV Use Case
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3 The business drivers
Drawing the attention towards economic and business drivers motivating a transition towards smart
grids, the present Section will investigate drivers facilitating the decision towards investments over
classical grids, and will further highlight business requirements providing useful feedback to the
technical realization, e.g. in respect to mitigating complexity or security threat disbenefits.
Originating from a value network representation (representing inter-firm business relationships) of
classical grids, the new value streams (in terms of monetary, resource, or other value exchanges) of
smart grids may substantially be different. Thus, creating a sufficient understanding of the business
change from “classical” electrical grids to smarter grids is necessary in order to examine business
advantages, i.e. drivers, arguing for the required transition. The necessity for investigating business
requirements may in addition be argued twofold: on the one hand the full exploitation of business
drivers may deserve the satisfaction of certain technical conditions (i.e. hygiene factors). On the
other hand, opposed to benefits of smart grids (business drivers), there may also arise costs (OPEX
and CAPEX) to be mitigated in order to render an attractive business environment.
The remainder of this section is structured as follows: Building on a common Value Network basis for
“classical” electrical grids and smart grids annexed in Section 9 (including entity (actor role) and
important value stream descriptions), business drivers are formed in Section 3.1. These business
drivers analyses will be conducted on a use case basis following a template proposal.
Correspondingly in Section 3.1.3.4 business requirements are collected and described from a
business driver point of view.
3.1 Business Drivers
This section aims at providing an analysis template for business drivers being applied to each of the
scenarios. We will first introduce a series of relevant business driver categories, which will be
instantiated for individual use cases.
3.1.1 Telco Sector
Before defining an appropriate template for the analysis of business drivers, we briefly discuss the
telco sector role in the smart grid context in order to capture business motivators in the energy
sector. The telco sector is of special interest for this investigation, as it complements the classical
energy sector roles in new smart grid business models and has not yet settled. The outcome will later
on be considered in the definition and application of the template.
There are several definitions of smart grid, but regardless of these definitions, the main characteristic
of the smart grids is the introduction and application of communications and information technology
in power grids. This will lead also to an increased usage of communication services, provided by Telco
operator, to cover the needs of the utility companies. Suitable communication technologies provided
by telco can be wireless or wireline, the first one mainly used in neighbourhood area network for
smart meter communication infrastructure because of easier and less expensive deployment, while
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the backhaul network to connect the smart meter head-end and the data aggregation points can
either be wireless or wired. Hereafter, we will focus on scenarios where connectivity is provided by
cellular technologies through M2M services because, although this technology introduces some
drawbacks, w.r.t. other wireless technologies it appears to provides the best answer in terms of
technical characteristics (coverage range, latency and reliability) at the lower cost and ease of
deployment [EEE12ZZ]. Regarding wired network and its adoption opportunities for smart grid, while
it has and will continue to have a place in utility market applications, several reports [NTS12 and
INT12] indicate a shift towards wireless technologies mainly driven by costs, difficult installations and
copper theft.
These scenarios foresee that the number of M2M device connections in the energy/utility sector will
grow from 22.1 million worldwide in 2011 to 1.3 billion in 2021. The CAGR (Compound Annual
Growth Rate) will be 50% during the 11-year period. Smart metering will be one of the fastest-
growing segments of the M2M ecosystem in terms of device connections during the next 8 years
[ANME12].
Figure 5 M2M device connections, energy and utility sector, worldwide, 2011–2021 [ANME12]
According to [ANME12], the growth in the sector is spurred by energy/utility companies’ need to:
respond to regulatory and legislative changes
access more granular demand- and supply-side data in near real time
constrain capital and operating costs
increase service offerings.
Limiting analysis to smart metering, [ANME12] list the following factors driving the adoption of M2M
based services within the energy/utility sector:
Reducing operating costs and increasing margins. Operators in the energy sector, including energy producers and distributors, are looking at ways to reduce costs. M2M devices help
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these businesses to improve processes such as meter reading, supply management and fraud prevention. As an example, better near-real-time management of electricity supplies can significantly reduce the cost of total energy production.
Providing accurate and timely data. M2M solutions are a way to remove human intervention from collecting data and making decisions, which will reduce costs [ANME12] and will help enterprises make better decisions more quickly by providing employees access to relevant business data in real time or near real time.
New revenue streams or product differentiation. M2M solutions allow energy companies to offer new services to consumers and other businesses. These new services might result in additional revenue streams or increased differentiation for manufacturers. Examples include home energy management, and residential and commercial security/surveillance solutions.
Renewed interest in connectivity due to Regulatory action and need to constrain costs. Building new-generation facilities is extremely complex and often politically difficult. Connectivity embedded in smart meters, homes and businesses helps the energy/utility sector minimise the need to build new-generation facilities and maximise customer satisfaction.
On the other hand the complexity of the M2M supply chain can inhibit the adoption of M2M
solutions in the energy sector. With M2M implementations frequently custom-designed, the overall
return on investment (RoI) of the solution is generally lower than that of other IT solutions.
Moreover government policy and regulation could have a deep impact on M2M adoption in energy
sector, depending on the commitment shown by governments and regulatory bodies for keeping
utility prices affordable, matching supply and demand, and encouraging energy conservation.
Connectivity represents almost 90% of M2M for CSP (role details see Section 9) revenue in the current market, but most of reports indicate that within three years M2M connectivity revenues will continue to grow, but new revenue streams will increase their importance for a sustainable profitability [INFO12]:
Connectivity (Communications services, associated communications hardware)
Professional services (Consulting, integration, software development)
Service level management (Security, demand response, performance management)
Business intelligence (Decision support, reports and alerts, analytics)
The same shift will apply also to business models and role that CSPs will play:
Today most CSPs function as M2M data wholesalers,
only one in every 10 CSPs actively runs revenue-sharing models with partners.
Fewer than one in 10 routinely offers service-level or application-based pricing for M2M. M2M stakeholders can agree that table stakes for market success are end-to-end service management and flexible billing for varied M2M applications and traffic profiles. Beyond these two priorities, however, for smart grids scenarios security and securing data delivery according to end customers’ service-level requirements is another priority to ensure. Conflicts Besides, the market data anticipating the raise of the M2M market and the interleaving of telco and energy sectors, the particular roles have not been settled. Energy companies may cooperate with
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telcos as “friends”/”partners” or may on the other hand exclude them from the smart grid business [ADL12], i.e., competitors. Generally, different entities may have different visions, expectations, and driving interests in the
raise of smart grids [ScTa12]. Communication services may in practice be provided by telcos, but also
by DSOs themselves. Fearing the disadvantages of being locked in by one or more telcos (high or
rising prices, know-how transfer [ADL12]), the classical top-down energy sector approach with full
control over the whole value chain may be preferred by DSOs. However, cost advantages through
synergies (“joint customer base and sales channels”, shared investment costs, etc. [ADL12]) for both
DSOs and telcos thus could not be utilized. [ADL12] recommends that energy providers carefully
consider their strategic positioning with respect to cooperation and competition alternatives for
communication services. Besides that, even telcos could become a competitor in the energy sector,
which may assist the finding of a cooperative equilibrium at the end.
Thus, we argue that conflicting business drivers may only be resolved at mutually beneficial
configurations, i.e. a stable equilibrium. We suggest designing scenarios facilitating high control for
DSOs, high cost synergies for DSOs and telcos, and adequate business involvement of dedicated
CSPs. This could for example be realized on top of full-Mobile Virtual Network Operator (MVNO)1
agreements between a trusted CSP and a DSO, which provides the following flexibilities to DSOs:
Possibility to replace telco provider by a competitor (some contractual limitations), if service or price
levels do not meet expectations
Complementation with own telco equipment possible (i.e., control over critical elements could be established)
Dedicated resources could be assigned to DSOs, which could substantially increase the control over the communication network (if technically enabled)
Besides synergies with the CSP, own investments could be made up by selling remaining resources to external customers, i.e., entering the “classical” telco business as MVNO
Besides that scenario, also regulatory measures could enforce a more direct cooperation, e.g. by
increasing the cost pressure on DSOs and CSPs, thus requiring the consideration of more synergies in
smart grids investment and operation.
3.1.2 Categories
Each listed category represents a specific area of concern that can be extended individually. These
categories extend the considerations of [EPRI10] and are presented here with a short description
listing high-level examples of more specific concerns. Not all categories may apply to each scenario.
1 http://www.nereoconsulting.com/pdf/SmartGridandMVNOs.pdf
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Figure 6 – A categorisation of generic business drivers
As illustrated in Figure 6, two main categories interrelating with most others are cost reductions and
revenue growth. The details are provided in the tables below.
Category Description & Means of Realization
(Here we describe by which means the area of concern can be addressed)
Costs Reductions Cooperation & Incentives: Improved cooperation with customers and suppliers
(business partners) is a significant source of cost reduction. In particular,
incentives for adequate supply/demand patterns may be used in order to
eliminate inefficiencies or even lead to customers/suppliers looking for
alternative business partners.
Entities: DSOs cooperating with energy generators and consumers on
adequate generation & demand levels; Retailers need to be incentivized to
reserve sufficient energy in advance; better integration of heavy users such as
charging stations in the grid stability picture
Increased Reliability: Improving reliability of service may bring a variety of
benefits also affecting cost levels. In the operative business, the compensation
payments (e.g. to business customers/partners) or even loss of customers may
be avoided. Cost advantages may be yielded by reductions of maintenance
costs (e.g. energy loss reduction primarily on MV level). In addition, further
aspects of product satisfaction or product attribute satisfaction like
convenience and quality may also affect customer satisfaction figures.
Entities: DSOs, CAMs (role details see Section 9), and also energy consumers
Wholesale energy trading efficiency: By an increased understanding of arising
supply and demand levels, utilisations can be attempted at the wholesale
market. In particular, unnecessary options deals may be avoided (or
downsized) or replaced by very dedicate futures purchases. This may on the
one hand save option fees and may on the other hand increase the supplies on
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the market.
Entities: Esp. CAMs and DSOs (more efficient trading due to better metering
information and thus forecasting)
Resource usage efficiency: The usage efficiency of invested resources, esp. by
smart control of renewable energy generation/use, may be improved. Thus,
fewer resources are used and less energy needs to be wasted.
Entities: Regulatory (may enforce efficient usage), energy generators
(reduced costs due to fewer raw material inputs), DSOs and CAMs (higher
stability due to reduced danger of shortages), energy consumer (“greener”
energy provisioned)
Claim management: Reduction of claims means a reduction of costs. Claims
could be a perceptually unreasonably/surprisingly highly energy bill (being
provided only on a e.g. yearly basis) or product dissatisfaction (i.e., outages).
Both types of claims may be targeted by smart grids where consumption
figures could be shared more regularly and outages (in increasingly more
difficult environments) are aimed at being further reduced in probability. This
factor also interrelates with customer satisfaction & loyalty, as well as with risk
management subcategories.
Please take note that the introduction of new technologies such as smart
meters may also require some claim handling in the transition phase. Thus,
ease of use for end customers is important – see business requirements.
Entities: Retailers and DSOs
Revenue Growth New Sources of Revenue: Newly designed information services may provide
added value to the customers leading to new sources of revenue. On the other
hand, the improved understanding may enable the provisioning of further
flexibility services, i.e., bearing risks of others etc. Finally, new/occasional
service offers could be provided, which could help utilizing fallow energy
resources, e.g., AC in public transport being automatically switched on
whenever there is no supply scarcity. (Please also take note that the utilization
of improved knowledge about customers and their consumption behaviour
may represent very valuable information e.g. for the advertisement industry)
Entities: Com. Service Providers (M2M services), DSOs/Retailers (dynamic
pricing), EV Charging Station Operators (satisfaction of more customer
requests), DERs (more DERs can be integrated in the grid), Vendors (new
equipment sold for metering or communication services)
Differentiation of existing services: Service differentiation, e.g. dynamic pricing
of energy at different times, may also allow energy providers to more
efficiently charge dynamically arising peaks. This may on the one hand
stimulate cooperation with business partners, and on the other hand generate
additional revenues beyond acting on the wholesale markets.
Entities: Retailers but also DSOs (and transitively CAMs)
Customer basis growth (existing resources): Due to a better forecasting of
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demand, as well as the shaping of actual demand and supply, supply levels may
be further exhausted by increasing the demand (new customers), trading of
resources (options, futures), etc.
Entities: Retailers and DSOs
The other categories are listed subsequently:
Category Description & Means of Realization
Risk Management
Efficiency
Risks are generally a considerable threat for business prospects. In smart grids,
this in particular complies with the risk management of energy and ICT
resources. At all the time it has to be ensured that sufficient supply matching
the demand is present.
Hedging: risk of investment (too low demand) hedged against put options or
risk of too low supplies hedged by call options on the wholesale market.
Reduction: Risks may be reduced e.g. by an improved understanding of
demand and supply patterns.
Sharing / Insurance: One may insure against energy (demand/supply)
fluctuations, e.g., by buying insurances. Insurances may cover monetary losses
or more realistically the bearing of the risk of ad-hoc energy demands, i.e.,
options or futures. A better understanding of available risks may lead to a
proper dimensioning insurances / risk sharing mechanisms. Risks may also be
shared among entities besides hedging mechanisms discussed above.
Entities: Mainly CAM, but also retailers and DSOs will have more
responsibilities regarding balancing the grid
Marketing &
Societal Benefits
The shift towards smart grids may be used for emphasizing the ecological
responsibility of firms (e.g. more renewables can be integrated). Especially in
the relationship with end customers, this may be a very important factor for
motivating such investments.
Smarter energy grids may provide better statistics allowing fine-granular
supply and demand analysis, customer inspection/relationship etc. This may be
seen as platform for doing business intelligence (knowing the customer base
for adjusting advertisements, product offers, etc.) as well as for the generation
of figures being used for PR purposes (e.g., consumption figures, saved energy,
reliability, etc.)
The reduction of greenhouse emissions, i.e. CO2, also poses benefits to the
society, i.e., lowered negative externalities (also see [EPRI10]). Thus, beyond
the direct business utilization, the society profits (also see regulation).
Entities: Retailers and DSOs, society
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Infrastructure
Efficiency
Delaying investments: the better understanding and proper utilisation of
existing infrastructure may allow the delaying of investments in future
upgrades. This may substantially affect the incurred costs, and may thus be
among the central drivers.
Infrastructure efficiency highly depends on the peculiarities of geographical
areas. Frequently most connection requests of renewable generation resources
come from rural areas where the grid hosting capacity and the communication
service availability are lower. On the other hands, the connection of flexible
loads (medium size prosumers and EV charging) is more relevant in urban areas
characterised by more reliable and oversized grid capacity.
(High precision) quality & energy demand/supply statistics: Improved
durability and quality statistics of deployed components may provide even
better selection of future devices
Entities: Mainly DSOs
Customer
Satisfaction &
Loyalty
Loyalty may be increased on two main axes, i.e., whitewashing customer
service, price or quality (reliability or information services), and obligations
(lock-in effects, long-term contracts). Endogenous whitewashing may occur
when intensified relationships with retailers or DSOs may automatically be
blandished by customers. Exogenously, whitewashing may be triggered by
dedicated advertisements & communication with the customers based on high
precision figures.
The customer satisfaction may be subject to economic aspects (is the price too
high? does the pricing scheme fit the needs?), self-control aspects
(consumption metering interrelated with current price), ecological aspects
(saving energy, green energy), (perceived) reliability, new information services
(where can I charge my car?), and trust (in energy grids, services etc.). By
allowing a more transparent communication with the customer a broad
majority of these factors could be addressed. The additionally provided new
capabilities enabling (dynamic) pricing and increasing reliability may further
contribute to suitable customer satisfaction levels.
Beyond that, customers may also profit from lower electricity prices, if smart
grids enable the more cost efficient integration of renewables.
Entities: Mainly retailers, consumers
Regulation &
Legislation
Smart grid investments and operation may be enforced and regulated by
official bodies or laws. Entities may in particular face the regulatory
enforcement of accommodation for broader scale renewable rollouts paired
with a required maintenance of adequate stability and power quality in the
grid. Thus, the retention of the current business model may require certain
technological and/or business process adaption to changing legal frameworks.
Entities: DSOs, CAMs and partially retailers and larger consumer/resellers like
EV CSOs, society (lowered greenhouse emissions).
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Together with further factors like Risk Management Efficiency and Infrastructure Efficiency the cost
related factors represent an economic dimension comparable to [EPRI10]. Additionally, the Marketing
& Societal Benefits extend the understanding of “Environmental” benefits as captured in [EPRI10].
Customer Satisfaction & Loyalty covers and extends “Reliability” advantages linked to smart grids. On
the other hand, “Security & Safety” aspects are interpreted as business requirements (see later), as
the raising complexity of smart grids require proper countermeasures itself on this axis.
3.1.3 Use cases
Based on the above-presented template, each SmartC2Net use case is analysed on a fine-granular
level. By picking relevant categories from the template, specific business drivers will be discussed,
e.g. smart grids may facilitate charging of more cars a day (revenue opportunity). On the other hand,
less relevant categories for specific use cases are completely omitted in the analysis. We will
additionally address conflicting business driver and related business conflicts per use case, e.g., DAC1
introduces a Business Driver conflict of the AMR/CEMS use case.
All use cases share the following high-level business drivers:
Risk Management Efficiency:
Due to improved metering, risk management can be further professionalized by receiving
better load forecasts, which lead to improved contractual agreements, i.e., insurances or risk
hedging agreements. These factors are typically immediately revenue-effective.
Marketing Benefits:
Improved argumentation towards society to better accommodation for renewables in the
grid, and thus probably raising share of “green” sources of energy
On a high-level, [EPRI10] suggests the following general and rather energy-sector-centric benefits per
actor group:
Energy sector: Reduced operation and maintenance costs, deferred capital costs, etc.
Consumer: Reduction of electricity costs and disbenefits from power interruptions (or
“power quality events”)2.
Society: Reduction of negative externalities
These generic drivers are subsequently extended by use-case specific details.
3.1.3.1 Voltage Control in MV grids
Business Driver Instantiation Conflicts
Costs
Reductions
The Voltage Control use case is mainly driven by cost considerations:
Improved cooperation between DSO and DER owners is a
significant source of DSO cost reduction
DVC1
2 These advantages may be seen in direct comparison to cases of extensive renwable rollouts without
smart grid assistance
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Minimised technical energy losses
Improving reliability, voltage stability and power quality of the
power supply service may bring cost cost benefits
Decreased outages means reduction in maintenance and claim
management costs
Optimised voltage profile reduces OLTC and DER costs of
operation
Ability to integrate more DERs may reduce pressure to act on
wholesale markets and thus may reduce costs
SmartC2Net may help DSOs to comply to the contracted terms
with TSOs and thus may be reduce costs inferred due to grid
instabilities (reliability issues) and/or charges (due to TSOs
having to act on the wholesale markets) – see risk
management
Entities: Mainly TSO, DSO cooperating with DER owners (generation
plants and medium size prosumers) on adequate generation &
demand levels
Revenue
Growth
The connection of DERs may enable the satisfaction of higher demand
levels, thus leading to potential electrification of new services. Thus,
this extending the grid business through higher demand levels. It also
requires extended communication services.
Entities: DSOs, CSPs
Risk
Management
Efficiency
Related to cost motivations, also risk management becomes of
interest:
Risks of over/under voltages may be reduced by relying on a
more precise grid monitoring, actors’ communications and
optimized set points
Specific focus on cyber security as a means of increasing the
efficiency of the cyber-physical risk management
Entities: TSO, DSOs, DER owners
(also see general drivers above)
Marketing (see general drivers above)
Infrastructure
Efficiency
The connection of DERs will allow to optimise the DSO infrastructure
efficiency in those geographical areas where grid overcapacity is
available – thus helping to delay investments in infrastructure upgrade
through more efficient usage.
Entities: DSOs
Customer
Satisfaction &
Loyalty
The increased acceptance rate of connection requests of DER to the
grid increases the customer satisfaction level, i.e. prosumer acceptance
Entities: DER owners (prosumers)
Regulation &
Legislation
DER connections to the grid have to guarantee compliance with
country-specific regulations reflecting the adopted business model and
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the grid code. DSO and DER owners need to meet revised regulations
requiring a shift to smarter grids, e.g. according to the new regulation
it is necessary that all active customers are endowed with a
communication system allowing the (real time) data exchange with the
DSO. This will allow the DSO to implement optimization logics and to
send all customers the signals implementing the actions (e.g.
disconnection) needed to guarantee the security of the whole power
system.
Entities: DSOs, DER owners, Regulators
DVC1: DSO operation constraints may decrease DER owners’ revenue.
3.1.3.2 EV Charging
The EV use case in particular targets the advancements over EV charging realisation on top of
classical grids. Explicitly, telecommunications, and as an effect of that, the solutions required in
SmartC2Net, are a result of the distributed character of the EV charging sub-system. Creating
decentralized decision support both at the LV grid, and at the charging station level has the following
advantages:
Business Driver Instantiation Conflicts
Costs
Reductions
No alarms are issued and power line enhancement costs are
deferred.
Grid operators may profit from overload avoidance in the LV
grid (due to charging station congestion) and in turn deferred
grid enhancements costs
Better estimates of demand due to smarter reservations may
lead to more efficient wholesale trading (lower overcapacity
and fewer intra-day trades, as well as improved risk
management)
Smaller dimensioning of charging stations may potentially also
result from load distribution optimizations
Entities: EV CS operators, DSOs, and CAMs (EV users may also profit
from lower prices)
DEV1
DEV3
Revenue
Growth
Due to optimized scheduling, the installed power and the
dynamic calculated available power is maximally utilized
On a high level, new revenue opportunities could be exploited
by e.g. renters/operators of parking lots or store operators that
may further provide charging opportunities in order to
differentiate over competitors or even directly increase their
revenues.
DEV1
DEV2
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Each charging station may also profit from an optimized
utilization of their charging capabilities by an improved
steering of customers to available resources (parking lots and
energy).
Due to the flexibility of the demand and of energy price
information, charging station operators can increase profits or
increase competitiveness by lowering their service prices
towards the customer
New information services may be realized on top of a more
capable smart grid platform
Entities: EV CS operators, InfSPs (e.g., E-Mobility Service Operator),
DSOs/retailers (selling all available energy), Com. Network Providers
(M2M services e.g. for charging stations and grid or connectivity in
cars)
Risk
Management
Efficiency
(see general drivers above)
Marketing In addition, the SmartC2Net grid may enable the broader role out of
EV charging stations and a broader coverage of charging demands due
to optimized balancing the grid. Thus, besides investment cost
reductions, CO2 reduction due to the transition from fuel-powered
cars may provide positive incentives.
Entities: Society, regulators, energy consumers, but also DSOs and
retailers may profit
(also see general drivers above)
Infrastructure
Efficiency
----------
Customer
Satisfaction &
Loyalty
Transparency by offering to broker between customers and
any supplier of charging services which best satisfies the
requirements of users (near to destination, price, availability of
resources, charging speed, energy mix, discount (loyalty
programs) (communications needed).
New information services such as the reservation of charging
resources before or during the trip (communication is needed)
while at the same time reserving a parking lot
No waiting times due optimal steering of customer flows
Decentralized operation of charging stations makes them less
vulnerable to single point failures of a central charging service,
i.e., higher reliability
Thus, positively attributing to the perceived convenience/quality and
reliability of using the EV charging service. The increased satisfaction
may also help to blandish price figures.
DEV2
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Entities: Mainly EV CS operators, DSOs and retailers (transitively also
EV users / energy consumers)
Regulation &
Legislation
Government incentives seem to expedite the broader usage of EV,
which thus drives the necessity for finding solutions to charge more
cars. Thus, by upgrades to smarter grids proactively regulatory or
legislator intervention may be avoided.
Entities: DSOs and CAMs
DEV3
DEV1: Customers may want to participate in cost reduction prospects, which may mitigate revenue
prospects through new services and more EV charging
DEV2: Customers may be reluctant to switch to other CSs without a monetary incentive or clearly
communicated benefits, otherwise customer satisfaction may not increase or may even be lowered.
DEV3: The political impetus for pushing EVs may entail the requirement for investing in smart grids
or antedating investments in smart grids, which may not be aligned to the plans of the energy sector
entities (in terms of costs etc.).
3.1.3.3 External Generation Site
Business Driver Instantiation Conflicts
Costs
Reductions
Reduction of claim management by avoidance of disconnection
of customers, and increased penetration of renewable energy
sources by maintained voltage profile on LV feeders
Minimize losses in MV grids while increasing the penetration of
renewable energy sources e.g. wind and PV in MV and LV grids
(we also kindly refer to Section 4.2).
Increase wholesale trading efficiency
Increase resource usage efficiency
Increase reliability of MV/LV grids
Entities: DSOs, Retailers, Consumers, Prosumers,
micro/intermediate/large DER, Network Owners/Providers
Revenue
Growth
New Sources of Revenue for prosumers,
micro/intermediate/large DER by providing ancillary services3
Service differentiations of existing/new services
New connectivity for smart grid actors provided by CSPs, e.g.,
by utilizing the network for providing tailored M2M services
and/or QoS-differentiated services
Entities: DSOs, Retailers, Consumers, Prosumers,
micro/intermediate/large DER, Network Owners/Providers
Risk
Management
(see general drivers above)
3 Paid services on top of energy generation such as voltage control or reactive power support, which
form a new type of business (business model) due to decommssing of large power plants. Thus, such services may gain in importance.
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Efficiency
Marketing Capability to integrate more renewables in MV/LV grids – in
particular the case of renewable energy sources i.e. wind and
PV, is studied in this use case.
Entities: retailers and DSOs, prosumers
(also see general drivers above)
Infrastructure
Efficiency
Reduce the need for grid reinforcement by better utilization of
existing grid
Entities: DSOs
Customer
Satisfaction &
Loyalty
Increase loyalty and satisfaction of end-users by increased
reliable power supply with renewable energy resources
Entities: Consumers, Prosumers, micro/intermediate/large DER
Regulation &
Legislation
New regulation and legislation for prosumers and their
interaction with the grid
Requirements regarding the interfacing between prosumers
and the system
Entities: Consumers, Prosumers, micro/intermediate/large DER
3.1.3.4 AMR/CEMS
Business Driver Instantiation Conflicts
Costs
Reductions
Enhance grid status information exchange below substations, which may raise the reliability of the grid, and thus may reduce costs
Peak shaving → Shift of demand at times where energy is available (reliability and thus cost effective; reduction in wholesale trading; reduction of required investment costs, etc.)
Minimize non-technical energy losses (illegal, unbilled energy consumption; also see paragraph on revenue)
Entities: Mainly DSO
Revenue
Growth
Minimize non-technical energy losses (illegal, unbilled energy consumption) → new fees are received
Com. Service Providers may profit from selling connectivity services for AMR/CEMS, while relying on infrastructure required for CPE connectivity, i.e., connectivity service bundles providing a new source of revenue with potentially limited investments required.
Entities: Mainly DSO and Com. Network Providers
DAC1
Risk
Management
Efficiency
(see general drivers above)
Marketing (see general drivers above)
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Infrastructure
Efficiency
Demand-response may delay infrastructure investments (e.g.
cables)
Customer
Satisfaction &
Loyalty
More frequent / more transparent feedback on consumption
and prices
Supporting customers in order to save energy and/or costs
Feedback mechanisms and home integration may blandish
price disadvantages
Yearly metering models may lead to imbalances of
consumption period and assigned prices, e.g., lower than
expected consumption in winter but higher in summer, as well
as to compensation payments at the end of the year (metering
and payment intervals may not be aligned), which can be
eliminated/mitigated with AMR/CEMS (customer interest &
satisfaction due to transparency and self-control capabilities). Entities: Mainly DSO and retailer may profit from increased
satisfaction (besides customers)
DAC2
Regulation &
Legislation
Regulators may enforce the deployment of smart meters, as practice in
Germany for example, and may also enforce load-dependent tariffing
schemes in order to promote energy saving behaviours of customers.
DAC1: Customer incentives may conflict with CSP’s revenue prospects, and thus need a proper alignment. DAC2: Customer satisfaction increase through improved consumption figures may not compensate required investments in smart grids and especially smart meters. Thus, this may have to be financed by other smart grid actors, probably DSOs. The discussed use case-specific business drivers are viewed as the motivators for the investigation of subsequent technical solution. Later on these drivers may serve as crosschecking or validation tool for evaluating how the architectural realization, i.e., the SmartC2Net solutions, support the realization of listed business drivers. This analysis has also illustrated the requirement for differentiating in particular smart grid services to be considered, as their driving forces may differ in their characteristic.
3.2 Business Requirements
Building on the description of business drivers, the present section investigates business
requirements – potentially providing implications on technical requirements – originating from a
business context. Thus, this section correspondingly provides use-case specific investigations on
technical properties that may be required to satisfy business needs. Such needs are caused by
business drivers for smart grids, or are dedicated to mitigate negative side effects (such as high
investment or operation costs of smart grids).
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3.2.1 Telco and energy sector interplay
A central requirement for the transition towards smart grids is the proper alignment of telco and
energy sector business objectives. Thus, this will be briefly discussed in this subsection and finally
provide implications on the business requirements template.
While DSOs may want to keep outmost control over their distribution network (including
communication services), CSPs are looking for a business case and may be able to utilize cost
synergies through the reuse of existing infrastructure. Thus, a fruitful cooperation implies the
following business requirements (also see dedicated business drivers section), which may, amongst
other technical solutions, be targeted by smart MVNO agreements:
Straightforward replicability of CSPs
DSOs’ possibility to deploy own communication infrastructure at critical locations
Cost efficient integration of DSO communication infrastructure with CSP infrastructure
Quality assurance, e.g., dedicated resources, access control, prioritization or other smart QoS
techniques
Efficient reuse of existing resources (e.g., MPLS rather than leased lines/own spectrum;
dynamic adaption to energy sector)
3.2.2 Template
The applicable categories for factors triggering business requirements specification are summarized
in Figure 7.
Figure 7 – A categorisation of business requirements
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Category Description & Means of Realization
Information Sharing
(Frequency, data sets
& access,
communication links)
Information Sharing: Requirements of communication links towards external
or internal business partners and/or between internal systems/departments.
Not only the frequency of data exchange is of high relevance, but also the
amount of data being required to be exchanged. Generally, we assume that
only the minimal set of data will be shared with business partners in order to
assure a proper functioning of the smart grid. Different data exchange and
access rules may apply to smart grid entities and (external) Information
Service Providers. Specifically of interest is the exchange between DSOs and
CSPs regarding current/expected performance and capabilities of the
network as well as the information dissemination of the grid status.
Another special case refers to the integration of Information Service
Providers building added value on top of smart grid interfaces. Information
services here refer to internally or externally provided added value services
(partially) utilizing information gathered or circulated in smart grids.
Data access: While the access of data needs to be restricted mainly
for security reasons (see dedicated category), the defined level of
data utilization may be subject to different degrees of market
openness: in order to allow the access of third party actors –
facilitating competition on information services – segmentation of
exchanged data would be useful (different information sets being
shared with different entities on different levels of aggregation)
Trust relationship: There must be a trust relationship between
partners accessing the data, data providers, and customers (trusting
in the proper handling of their data). Unreliable partners need to be
removed, and the data access design should limit the required trust
level as much as possible.
Entities: All actors, esp. Information Service Providers, E-Mobility Service
Operators, Com. Service Providers, and DSOs.
Investment
Efficiency
Investments in smart grids (and individual systems or components) should be
kept as low as technical feasible. Thus, cost efficiency is required in order to
manage a successful transition towards smarter grids.
Entities: Esp. DSOs but also Com. Service Providers (w.r.t. revenue
prospects)
Efficiency of
Interaction
Market or system interactions or price adjustments may be subject to
different timescales. Thus, economic requirements for maximum timescales
or granularities may exist (in respect to dynamic pricing).
System/Market Interactions: The granularity of interactions between
systems or market places may be subject to service/use case requirements or
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customer demands, which may substantially influence the practical
realization of use cases.
Entities: Retailer (on wholesale market), CAM (on wholesale market and
with retailer), and esp. DSO (with generators, consumers, and CAM w.r.t
metering information exchange)
Possibility of (dynamic) pricing / service differentiation: The requirement of
allowing (dynamic) pricing (or comparable differentiation of existing services)
of particular resources
Entities: DSO (in cooperation with retailers)
Flexibility of
Deployment (e.g.
plug & play)
Limited effort: The transition to smart grids should be accompanied
by limited deployment or behavioural adaption efforts
Plug & Play: The reduction of deployment complexity in terms of
required know-how is of high importance, i.e., a "plug & play"
paradigm in lieu of required individual adaptions. Also the
complexity for customers should be limited towards the transition to
smart grids in order to keep claim management efforts minimal. New
features/technical capabilities should thus optimally be self-
explanatory.
Entities: DSOs & Com. Service Providers (limited CAPEX for smart
grid investments), Information Service Providers (easy access to
data), EV Charging Station operator (w.r.t integration in smart
grids)
Environmentally
Sustainability
Energy-aware components, e.g., having the capabilities of shutdowns under
low loads, are required in order to mitigate cost increases as well as in order
to support the ecological argumentation of smart grid role outs towards
customers or the society in general.
Entities: all, but esp. DSO & Com. Service Providers
Improved Metering A key element for gathering information in smart grids is metering (on the
customer side as well as in the grid). Thus, metering information provides a
fundamental basis for business considerations or utilizations of gathered
data.
Control/Validation of business/legal agreements: A more precise validation
of business or legal agreements may be enabled
Entities: CAM, DSO and retailer
Basis for Forecasting: Currently present or historic demand / supply patterns
may be useful for forecasting subsequent deviations (especially regarding
seasonal, daytime, etc. effects)
Entities: CAM and DSO
Localization (of faults): Metering information may provide a good basis for
localizing events like faults, stressed components, deviating demand/supply
patterns etc.
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Entities: DSO
Basis for Statistics: Gathered information may be utilized for business needs.
In particular, business intelligence (classification of customers, customized
offers, etc.) and PR/Marketing (communicable figures etc.) considerations
may play a big role.
Entities: Retailer (and DSO?)
Basis for Shaping: The metering information will be useful for providing a
basis for shaping demand and supply (demand-response) via automatisms
(i.e., consumer devices adapting their energy consummation),
feedback/suggestions (e.g., alternative charging station suggestions or high
load indications), pricing, etc.
Entities: Mainly DSO
Incentivizing
Customers
Customer demands regarding the usage of service, e.g., localization of
available charging stations, have to be met in order to successfully realize
SmartC2Net use cases. These factors may be assisted by technical or
monetary incentivization of customers.
Entities: Esp. DSOs
Operational
Efficiency
Originating from key business driver, the maintenance as cost factor is a very
import prerequisite towards the transition to smart grid systems. On the one
hand, smart grids should only add limited maintenance effort to existing
grids. On the other hand, smart grids should contribute to lower
maintenance costs of classical grid components, e.g., due to faster recovery.
Reliability (outages):
o Durability of components (years): The durability of individual
components is in important factor for reducing outages, but
also reducing overall maintenance costs.
o Redundancy & Fault Tolerance: The failure of one
component should be of limited/minor effect to the overall
grid. This may be targeted by suitable degrees of redundancy
or component failure tolerance
o Quality of Network/System: Besides durability constraints,
communication network quality (or quality of other systems)
may decrease the required maintenance effort in terms of
human intervention.
o Alerts:
Component failure: Automatic and precise (e.g., in
terms of localization) notifications about component
failures should be provided
Component overload: Automatic and precise
notifications about highly stressed components may
be provided
Self-healing: Recoverable failures (e.g., software) of
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components/control system/etc. may be assisted by automatic self-
healing processes. This may essential reduce the human effort in
maintenance
Time to recover: Outages or limited service usages may be very
costly. The time to recover from failures is thus critical.
Entities: DSOs and Com. Service Providers
Information Security Confidentiality: The business information gathered or circulated in
the smart grid has to be regarded as confidential to external and/or
competing actors. Competitive information needs to be protected
throughout the smart grid.
Privacy: The customer information collected or circulated in the
smart grid has to be protected. In particular, careful handling of
information exchange with other entities is required: there should be
the capability to blur unavoidable data exchange (e.g., due to
technical or legal reasons), i.e., elimination of identities, meaningful
aggregation of information, segmentation of information sets etc.
Avoidable data exchanges (besides judicial or social restrictions)
should serve a business interest of the information contributing
party.
Information Integrity and Availability: The requirements to be able
to trust on information gathered through metering and/or
exchanged with partners or other systems, or circulated in the own
network.
Entities: All (as all are using communication services)
3.2.3 Use cases
By picking relevant categories form the above-presented template each use case is specifically and
fine-granularly addressed. Thus, the present section will provide qualitative and use-case specific
feedback towards the analysis of requirements. Additionally, we will again investigate business
conflicts associated to stated business requirements of each use case, e.g. RAC1 introduces a
Business Requirement-related conflict for the AMR/CEMS use case.
Please, note that all use cases of course immanently require cost efficiency for a successful
realization, e.g., typically combination of connectivity services for end customers (Internet access)
may be aligned to the realization of smart grids to keep costs low and/or strengthen revenue figures.
We may also state the following high-level business requirements being shared by all use cases:
Efficiency of Interaction:
Higher dynamicity of interaction, information exchange and trading:
o Grid resource trading in seconds
o Supply-demand balancing in milliseconds -> thus balancing reserves like batteries
required more intensively
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o Pricing updates in milliseconds in order to provide meaningful behavioural adaption
incentives (mechanisms avoiding oscillations in the system may be required)
More fine-granular interaction and cooperation
More fine-granular control over the distribution grid
o Incentives / compensation mechanisms (w.r.t. contracts and information exchange)
for balanced / unbalanced energy demand & supply by retailers
More systematic integration of DER supply-levels, retailer energy sales, customer behaviour
and actors balancing the grid, i.e., DSO, CAM, TSO.
Improved Metering:
More fine-granular metering capabilities
o Providing means for require fewer flexibility & reserves
o Better forecasting of demand and supply levels in order to make reservations earlier
(at a cheaper point in time)
3.2.3.1 Voltage Control in MV grids
Business
Requirements
Instantiation Conflicts
Information
Sharing
Communication links between DSO and TSO, Aggregators, InfSP, CSP,
and between DSO systems and networks (e.g. metering, SCADA and ICT
infrastructures)
Investment
Efficiency
-------------------
Efficiency of
Interaction
(see generic business requirement above)
Flexibility of
Deployment
Flexibility in implementing new DER connections is required. The role
of standards is particularly relevant
Evniron.
Sustainability
Environmental sustainability is relevant in view of energy source plans
and global economic strategies
Improved
Metering
Improved metering capabilities provide more accurate generation and
load forecasts (also see generic business requirement above)
Incentivizing
Customers
Favourable contractual conditions (e.g., electricity costs) through a
more efficient integration of DERs or tax deductions for installation
costs may support the transition towards smart grids.
Operational
Efficiency
The voltage control is tightly coupled with efficiency of operation of the
grid and its components, i.e. advanced voltage control is required
Information
Security
Availability and integrity of grid monitoring and voltage control
information flows is essential
3.2.3.2 EV Charging
Business Instantiation Conflicts
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Requirements
Information
Sharing
Information Sharing: On a high level competitive data needs to be
protected from competitors, which includes occupancy rates. On the
other hand, the privacy of end customers needs to be protected.
All involved entities inherently require communication services
for their coordination.
Direct and convenient interaction between end customers and
CSOs is required in order to find suitable charging stations in
the proximity of most customers. Thus, E-Mobility Service
Operators (or comparable information services) require access
to reliable forecasts whether a CS will be able to meet the
energy demands of a requesting EV in a certain timeframe.
However, the charging station should not directly exploit load
levels allowing a long-term monitoring of financial success.
Thus, we for example envision the following process chain
avoiding iterative requests for data collection purposes:
Car request (energy demand, area, price constraints) → E-
Mobility Service Operator one-by-one contacts CSs → positive
reply means automatic and compulsory reservation of the
energy slot (i.e., no-show fee seems to be required)
Moreover, due to the sharing of customer demand levels the
role of an Aggregated EV Charging Infrastructure Management
cannot be played by direct competitors and may only be
shared with trusted partners. We, thus, suggest linking this role
with energy aggregators or creating an Aggregated EV Charging
Infrastructure Management instance for each CS chain.
CSOs require an on request communication link towards DSOs
and their energy retailers to make sure that sufficient energy
can be distributed in order to satisfy present EV requests.
Whenever minimum loads are guaranteed to users, the DSOs
need to immediately update the information being
communicated to other (requesting) consumers. As there may
still be a certain fluctuations of individual demands, it is
advised that CS request a minimum energy level plus an
epsilon as risk hedging factor for the satisfaction of own
customers’ interests.
In order to allow pre-planning of both the distribution grid load
levels and the CS utilization, customer requirements should be
characterized by minimal and maximal energy charges
requested
User data – especially personal data, consumption pattern, reservation
details, and payment information – should only be exposed to a limited
REV1
REV2
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number of entities or optimally be handled anonymously (optimally up
to a single actor like the CSO or an InfSP). Thus, user data is only
forwarded to entities absolutely requiring this information and may in
the optimal case be anonymised.
Investment
Efficiency
----------
Efficiency of
Interaction
The charging is currently a slow process with duration between 30
minutes and 3-4 hours. A time accuracy in the schedule in the range of
minutes is therefore sufficient. Therefore the charging capacity
planning will have a granularity in the range of e.g., 5-15 minutes.
Charging stations require the latest price signals (wholesale markets,
aggregators) and available power profiles (calculated by the LV grid
controller; DSO interface) in order to optimize the utilization of
charging slots. In addition, an interaction between the charging station
(CSO) and the aggregator, for reserving/purchasing the energy is
required (also see generic business requirement above).
Flexibility of
Deployment
----------
Environ.
Sustainability
----------
Improved
Metering
Related to higher efficiency of interaction, frequent updates of
metering information again in the granularity of 15 minutes are an
essential prerequisite for the effective steering of customers and
efficient reservation of resources (also see generic business
requirement above).
Incentivizing
Customers
Requests consisting of a minimum and maximum (full battery) amount
of energy have to be considered in order to align energy demand and
price expectations to available resources and wholesale trading prices
in the energy supply. While due to congestions, fluctuating grid
conditions, the maximum request may not be satisfiable, the minimum
charge request should be met in any case.
Operational
Efficiency
----------
Information
Security
Secure handling of customer reservations (avoidance of manipulation,
and privacy) and wholesale market interactions is essential.
REV1
REV1: Required information sharing may conflict with the protection of user information and
anonymisation especially w.r.t. to the optimal steering of customers.
REV2: Customers may not be aware of their needs, especially hours before the usage. This may be an
immanent EV charging problem, but especially relates to the problem of reservation and pre-
planning. Thus, certain flexibilities for increased or reduced energy charging may have to be found,
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e.g., by proper integration with information services allowing an updating of plans within certain
bounds.
3.2.3.3 External Generation Site
Business
Requirements
Instantiation Conflicts
Information
Sharing
DSOs will collect and process all data from end-users. Specific data will
be provided to relevant actors using different comm. networks. There
will be a need for a legal framework regarding the access and usage of
data.
Entities: All actors, esp. Information Service Providers, E-Mobility
Service Operators, Com. Network Providers, and DSOs.
REG1
Investment
Efficiency
Software platform allowing efficient deployment and interaction over
communication infrastructure with actors.
Efficiency of
Interaction
Adaptation of communication to fit current network condition without
changing interface for DSO or other entities accessing data from end-
users (also see generic business requirement above).
Flexibility of
Deployment
Plug&Play will require demanding connection requirements and
standardization for both grid and networks.
Environ.
Sustainability
Reduction of power losses due to a more careful handling and control
of assets
Improved
Metering
New metering functionalities will be required
o faster update rates for exchanged data
o possibility for delay estimation (network level)
(also see generic business requirement above)
Incentivizing
Customers
Potential of providing detailed information of energy
consumption/production to individuals, which may allow end users to
for example become aware of own consumption.
REG1
Operational
Efficiency
----------
Information
Security
----------
REG1: Access and usage of data may be strong concern for customers, whether end users or
enterprise customers.
3.2.3.4 AMR/CEMS
Business
Requirements
Instantiation Conflicts
Information
Sharing
Information sharing between the customer energy management
domain and the service domain (DSO, Supplier, 3rd Party) is essential
business requirement and may additional technical infrastructure (at
RAC1
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gateway) and may require careful additional regulation
Investment
Efficiency
----------
Efficiency of
Interaction
(see generic business requirement above)
Flexibility of
Deployment
No decline of comfort or reliability of supply for customers (they need
not care about underlying infrastructure), i.e., influence to end users’
usage habits (manual) may be kept as minimal as possible or may be
assisted be compensatory measures such as monetary incentives or
supporting systems/automatisms (it has to be ensured that
automatisms cannot be used to the disadvantage of customers).
Consumption figures (visual indications) should be easy
understandable for end users and required human intervention should
be kept.
Evniron.
Sustainability
----------
Improved
Metering
(also see generic business requirement above)
Incentivizing
Customers
Access to CPE may require incentives for the customers, e.g., by
receiving cheaper or even free Internet access etc. (provided by telcos
or grid operators themselves), in order to create a mutual interest of all
actors.
RAC2
Operational
Efficiency
----------
Information
Security
Especially protection of energy consumer data is essential, i.e., privacy,
in order avoid legal or societal blockage.
RAC1
RAC1: More precise information of customer demand patterns is very valuable information esp. for
DSOs, which may thus be reserved towards actions protecting customer information. Anonymisation
and privacy protecting architectures may be supportive for aligning conflicting interests.
RAC2: CSPs may require to be subsidized for providing such offers, which may not be in line with
other smart grid actors’ intention.
Despite the broad conformity across use cases, a wide range of flavors is represented by the chosen
use cases. Thus, the identified use case-specific business requirements and drivers will serve as basis
for cross-validation dimensions during the formulation of the architecture and evaluation phases in
later stages of the development.
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4 UC details
In Chapter 2 an overview of the four Use Cases is presented. In this chapter a more deep description
is provided in order to highlight the ICT aspects. The communication components and the relevant
networks are hereby reported and the specific anomalous scenarios addressed by each Use Case
identified. In particular we distinguish the accidental faults from the intentional malicious attacks.
The type and the characteristics of the abnormal scenarios depend on the specific information flows
and architectures addressed.
4.1 Voltage Control in Medium Voltage Grid
4.1.1 Objective
The introduction of Distributed Energy Resources (DERs) can influence the status of the power grid.
The behaviour of DERs can affects the capacity of the DSO to comply with the contracted terms with
the TSO and directly the quality of service of their neighbour grids. DSO has to face with units whose
behaviour is both unknown and uncontrollable and investments on conventional reactive power
control devices in substations may become ineffective. Automatic voltage regulations limited to the
OLTC (On Load Tap Changer) of the substation transformers, as usually operated in passive grids, may
be not sufficient to meet the supply requirements established by the norm EN 50160. This difficulty
to meet the contracted terms and the quality of service standards not only could be transferred into
charges to the DSO, but also affects the TSO operation because the scheduled voltages at grid nodes
could not be observed and voltage stability problems cannot be managed properly.
In order to maintain stable voltages in the distribution grid the Voltage Control function is
introduced. This main goal can be extended in order to achieve other important objectives as supply
ancillary services, minimize the cost and the KWh consumption, provide reactive power support for
distribution buses, reduce energy losses and provide compatible combinations of the above
objectives. The specific aim of this UC is to define a ICT architecture for the Voltage Control function
suitable for the security analysis. The main functionality of the medium voltage control function is to
monitor the active distribution grid status from field measurements and to compute optimized set
points for MV DERs, flexible loads and power equipment deployed in HV/MV substations.
The voltage profile optimization is reached by controlling reactive and active power injection by
distributed generators, flexible loads and energy storages, and setting On Load Tap Changers (OLTC),
voltage regulators and switched capacitor banks. Costs of control actions and load/generation
forecasts in the area have to be taken into account to select the appropriate control strategy
[UC200].
Figure 8 schematizes the Voltage Control Function with the inputs and the computation of a Voltage
profile in order to send set points to customer and utility devices.
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Third party MV DER Distributor’s device
Voltage Profile
Grid Topology
Fieldmeasurem
ent
Marketprices
ResourceOperation
costs
TSOsignals
LoadForecast
Voltage Control
Function
GenerationForecast
Figure 8 - The Medium Voltage Control Function
Voltage profile and power flows in active distribution grids are changing dynamically, mainly because
of the stochastic production of renewable sources. The power injected by distributed generators can
overload feeder segments or lead the voltage beyond the limits in some parts of the grid. In order to
guarantee the correct voltage value at each customer site, the voltage profile of the distribution grid
is continuously monitored and optimized using the available grid flexibilities.
The optimization function can be implemented in a delocalized site for the selected area. Considering
the hierarchical architecture of the electric grids, a controlled area is a Medium Voltage (MV) section
of the grid, typically underlying a primary (HV/MV) substation and having points of common coupling
with distribution buses or the upper level grid. In this UC, the optimization function is performed by
the Medium Voltage Grid Controller of HV/MV substations.
At the border of the control zone the function can manage the area as a technical Virtual Power Plant
(VPP) and the main voltage optimization criteria can be extended to supply ancillary services to the
upper level grid, contributing to the stability of the electric power system. The function then
improves the spatial reactive power balance as well as the voltage quality in electric distribution
systems and also the spatial balance of the active power.
In a generic case, the optimization process takes into account combinations of technical/economical
objectives and constraints, including requirements on power exchanges at points of common
coupling with the higher-level grid. The optimization algorithm is not detailed in this generic use case
and it is assumed to be performed by an ICT component within the substation control network. Only
the actions derived from the optimization function are considered in view of their communication
needs.
As part of the coordinated optimization within the substation, suitable devices for control actions are
selected. Depending on the particular grid controlled area where the voltage control is applied and
on the optimization objectives, some generation/load units can be controlled either directly by the
DSO Controller or via the Flexibility Operator (in the following referred with the term Aggregator).
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After any change of an equipment state, either due to a substation request or to a local automatic
action, the substation is notified about the new state or operating point, including the information
on available regulation ranges.
The application includes the controllable power equipment, distributed generators variables and
issue corresponding signals to these variables in the closed-loop control sequences.
If during the execution of the optimal solution, the topology of the grid changes, then the application
is interrupted and the solution is re-optimized. If during the execution some operations are
unsuccessful, then the solution is re-optimized without involving the malfunctioning devices. If some
of the controllable devices are unavailable for the remote control, then the solution does not involve
these devices but takes into account their reaction to changes in operating conditions.
4.1.2 Architecture and Sequence Diagrams
In order to analyze the communication aspects of this use case, we need to highlight the main
interaction between the elements involved. The main control and communication components are
presented in Figure 9.
TSO Control Network
DSO/DMS
TSO/EMS
Generation Forecast
IEC
60870-5
-104
MVGC
IEC 61850
Load Forecast
IEC 60870-6
(ICCP)
IEC 61968-100
IEC
61850
IEC 60870-5-104
IEC 60870-5-104
IEC 60870-6 (ICCP)
IEC 61968-100
IEC 61850-8-1 (MMS)
Aggregator
IEC 61850-8-1
(MMS, IP GOOSE)
IEC 60870-6 (ICCP)
IEC 61968-100
DSO Control Network
OLTCCapacitor Bank
Substation Automation System
DER
Flexible Load
DSO Enterprise Network
Figure 9 The UC Architecture
The Medium Voltage Control Use case involves communications through components inside the DSO
area, but also exchange of information with systems outside the DSO domain.
The TSO Control Center interacts through the TSO Control Network and the DSO Control Network
with the DMS through a permanent link in order to be able to send, if necessary, the signal that
triggers the execution of the voltage control function.
In order to compute an optimized voltage profile the algorithm needs different input data provided
by different actors. The DMS forwards the information from these components to the Medium
Voltage Grid Controller. In this way the control center – primary substation communications are
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reduced. The Aggregator provides the load and generation program and the ancillary cost to DMS via
the DSO Enterprise Network.
Also the Load and Generation forecast interact with the DMS through the DSO Enterprise Network.
The DMS sends /receives information to/from the Medium Voltage Grid Controller through the DSO
Control Network.
The Medium Voltage Grid Controller is connected through the Substation Automation System with
the Capacitor Bank and with the OLTC in the substation LAN. DERs and Flexible loads communicate
with the Medium Voltage Grid Controller via the DER /Flexible loads Control Network, possibly
deploying heterogeneous communication technologies available in different geographical areas.
In particular it is possible to identify the following different networks as depicted in Figure 10 :
NW1: Wired LAN local to substation, distinguishing different network segments that
corresponds to separate control layers, e.g. station, bay and process layers
NW2: Wireless/wired WAN that may use commercial cellular or private wireless technology.
This network connects the substation with the DER sites
NW3: Private wired WAN. This network connects the DSO Operation Center with the
Substation. It may be based on dedicated communication services via wired WAN
NW4: Wired LAN local to DSO Operation Center, distinguishing different network segments
that corresponds to separate operation layers, e.g. DMS and MDMS
NW5: Wired WAN. This network connects the TSO Center with the DSO Operation Center. It
may be based on dedicated communication services via wired WAN
NW6: Public IP. This network connects the Aggregator with the DSO Enterprise Center
NW7: Wired WAN. This network connects the DSO Operation Center with the DSO Enterprise
Center. Most probably it will be based on dedicated communication services via wired WAN.
TSO Center
Aggregator Site
DER SiteDSO/Customer
DSO Operation Center
DSO Substation
FieldSubstation
AutomationSystem
DMS
Flexible load siteDSO/Customer
DSO Enterprise CenterEnterpriseSystems
NW6
NW5
NW7
NW3
NW2
NW4
NW1 MVGC
Figure 10 Voltage Control – Communications
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Figure 11 Medium Voltage Control Sequence Diagram
The sequence diagram in Figure 11 shows the exchange of messages between the actors. The DMS
collects information from the Generation Forecast, Load Forecast and Aggregator and forwards them
to the Medium Voltage Grid Controllers. The TSO can send signals to the DMS that dispatches them
to the Medium Voltage Grid Controller. The distributed energy resources, flexible loads and
distributor’s devices (OLTCs, Capacitor banks) provide measurements to the Medium Voltage Grid
Controller.
Once obtained all the required information the Medium Voltage Grid Controller, if necessary due to
the estimation of the state of the grid or for optimization purpose, computes the set points. These
values are sent to the field devices in order to stabilize the voltage.
4.1.3 Fault/threat analysis/scenarios
In the analysis of the attack scenarios different networks can be taken in consideration, in this Use
Case the Medium Voltage Control function is taken as central element and the related
communication networks are addressed. In particular the input and output data flows are
considered.
The two main areas of data exchange are the DSO Control Network (connecting the DMS with the
Medium Voltage Grid Controller) and the DER Control Network (connecting the Medium Voltage Grid
Controller with the DERs).
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After the identification of the critical networks that will be addressed, we focus our attention on the
possible effects that the attack can cause to the control function. In general the attack scenarios can
affect the following security properties [IEC 62351]:
Confidentiality: preventing the unauthorized access to information
Integrity: preventing the unauthorized modification or theft of information
Availability: preventing the denial of service and ensuring authorized access to information.
In the Voltage Control Use Case integrity and availability represent the most relevant security legs.
The availability is threatened by the possible loss of data or commands, while the introduction of
possible fake data or the execution of possible fake commands can have effect on the integrity of the
control function.
For each UC network, we can initially consider two macro categories of attack effects: loss of good
messages (effects on availability) or introduction of fake messages (effects on integrity). Moreover it
is possible to identify two types of traffic: periodic and asynchronous. Combining this information the
schema of possible attacks depicted in Figure 12 can be completed where three dimensions can be
observed: type of traffic (Periodic or Asynchronous), network addressed (DSO Control network or
DER Control network) and the security propriety effected (Integrity or Availability).
Availability
Integrity
Periodic traffic
I: Costs, Generations
Forecast, Load Forecast
Measurements (field)
O:Measurements, states (to DMS)
I: Measurements P,Q,V
DSO Control Network
Asynchronous traffic
I: TSO signal, TopologyO: Setpoint
O: Setpoint P,Q,V
DER Control Network
Figure 12 Possible attack scenarios to the Voltage Control function
In order to reduce the analysis space, a selection criteria based on the evaluation of effect criticality
has to be applied to all the possible attack combinations in Figure 12, resulting in the following attack
cases:
DoS Attacks to DER (gateways). The traffic between DER and Voltage Controller is perturbed
and some DER measurements are not able to reach the Voltage Controller.
DoS Attacks to Substation (gateways). The traffic between the Voltage Controller and the
DMS is perturbed; some DER and SCADA measurements are not able to reach the DMS any
more.
Fake DER setpoints. Either an (additional) fake setpoint is sent to DER, or a legal setpoint is
intercepted and modified with wrong set point values
Fake TSO signals. A fake TSO signal is sent to the Voltage Controller.
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A (flooding-based) DoS attack performed against DER or Substation gateway may perturb the
periodic traffic. The percentage of lost messages could allow to evaluate the possible effects on the
voltage control. On the other hand the sending of a fake message performed in order to implement a
fake setpoint or a fake signal, or to alter an existing message may cause instability or DER
detachment. The observed effect of the fake setpoints sent to DER is an enabling factor for the
intrusion detection.
In section 10.1.4.2 of the template (see Annex B - UC templates) some anomalous scenarios of the
Voltage Control function are analyzed with focus on the effect of the attack scenarios introduced
above.
The global impact of such cyber attacks to the Voltage Control functions on the supplied power
depends on the grid size and the amount of distributed generation, both these factors varying on a
geographical base.
By focusing on the Italian target of integrating an amount of renewable energy of about 40 GW
within 2020 [Petroni12], the distribution grid development plan will require the building of about
10% new HV/MV substations. The analysis of the attack impact on the supplied power depends on
the control network topology on the top of the power grid structure. By applying an extreme case
approach, the impact value associated to future smart grids endowed with the Voltage Control
function depends on the extension of the attack effect. For example, an attack to the DER network
could cause the disconnection of all the generators connected to the MV feeders of a given
substation (that means more than 100MW in the extreme case of the Center 25 in the Figure 13).
From the same impact analysis it results that an attack to the substation networks could be able to
disconnect one or several substations (e.g. less than 1 GW), while a control centre attack, causing the
disconnection of all the substations in a given control centre, could count 6 GW of unsupplied power.
Figure 13 Estimated RES Power per Substation (2020)
By mapping such impact values on the power scales identified by the SGIS working group [SG-CG/IS
12], it results that the impact of those cyber attacks to the communications of the Voltage Control
functions may be associated, respectively, to the Medium, High and Critical impact levels.
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4.2 External generation site
The Use Case is focusing on demonstrating the feasibility of controlling flexible loads and renewable
energy resources in LV grids over an imperfect communication network. The flexibility provided by LV
grids for upper hierarchical control levels is also investigated. The case is potentially disconnected
from the external MV grid, therefore the external generation site. In the following we elaborate this
use case.
4.2.1 Objective
With the introduction of significant decentralized energy production from wind and photovoltaic
plants in the LV grid along with energy storage as illustrated in Figure 14, new problems arise. In this
setting the low voltage grid control should preferably be able to: 1) control the voltage profile along
the low voltage feeders, 2) optimize MV grid losses; 3) optimize energy cost; 4) aggregate the
flexibility of LV and MV assets that can be used as an input to the MV control and distribution
management system (DMS). The grid operation should in this matter be resilient to faults and
performance degradation in the public communication lines between the low voltage grid controller
and the assets in the electrical grid with special focus on the low voltage side, hereby limiting the
effect of changing network conditions on the electrical grid performance. This means that the use
case also includes mechanisms for adapting the communication to events in the network that
challenge the communication and the quality of the data exchanged between the controlled and
controlling entities.
Under these settings, different sets of actors will interact for the two focus points:
- Technical flexibility and performance: Resilience of control towards faults and congestions in
communication networks.
- Commercial feasibility and flexibility: Aggregation of generation and demand (abstraction of
models).
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Primary Substation
Automation&Control
MVGC
ProsumerLarge DER Large DER
HV Grid
HV
MV
MV
LV
Prosumer
Consumer
Interm. DER
Consumer
MicroDER
SME
Farm
SME
EnergyStorage
…
MV
LV
...
...
...
...
MV
LV
Use Case 2.3
Prosumer
Retailers
DMS
TSO
ForecastProviders
Markets
AggregatorsMV/LV
WAN
AN
Technical Flexibility
&Performance
Commercial Feasibility
& Flexibility
AN Provider(s)
AN Provider(s)
WAN Provider(s)
Secondary Substation
Automation&Control
Secondary Substation
Automation&Control
Secondary SubstationAutomation & Control
LVGC
Figure 14: Overview of external generation site use case
Figure 14 also shows the proposed communication network structure imposed on the power grid.
The use case includes control of LV grid components, such as households, farms, PV’s, local wind
turbines, etc. as well as MV grid components such as larger refrigerator systems, wind farms etc. To
achieve this communication is needed to ensure proper transport of measurement and control
signals to assure proper control of the assets in the grid. Thus, the electrical grid includes both LV as
well as MV grid. The communication network is split into three categories: 1) the access network
(shown in orange) connects all actors in the low voltage grid; 2) the dedicated wide area network
(shown in blue) which is a high performance dedicated network for grid control; 3) the wide area
network (shown in red) connects the rest of the middle voltage actors.
The definitions for distributed energy resources used for this Use Case are defined in the table
below. These definitions take into account the voltage and current at the connection point as well as
the power rating of the device.
DER Definition Voltage Ratings
[kV]
Current Ratings
[A]
Installed
Capacity
[kW]
DER Type
Micro DER < 1 <16 < 5 DER at Household level e.g.
micro CHP, PV system, wind
turbine, energy storage,
Intermediate DER < 1 > 16 5 < …< 500 DER connected to low
voltage feeders. Examples:
standalone systems e.g. PV
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panels and heat pumps,
single wind turbine, battery
storage, charging spot for
EVs, etc
Large DER > 1 > 16 > 500 DER connected to medium
voltage grids. Examples:
wind or PV power plants,
Combined Heat and Power
plants, Supermarkets with
refrigeration systems and
charging stations for EVs,
etc.
Market(s)
Data Transport(WAN)
Data Transport(AN)
Control of assets
Retailer
DSO
TSO
ForecastProvider(s)
AggregatorTechnical (MV/LV)
Medium Voltage Grid Controller
Low Voltage Grid Controller
Prosumer
Consumer
Micro DER
WAN Provider(s)
Network
performance
change
Network
congestion
Lost network
connectivity
Network
performance
change
Intermediate DER
Large DER
DMS
AN Provider(s)
ProsumerNetwork
congestion
Lost
Network
connectivity
Figure 15: Overview of use cases – and fault/error cases.
The diagram in Figure 15 illustrates the use cases found in the external generation case. The key
functionality is to keep the grid operational in both technical and commercial sense as already
mentioned which is the key focus of Control of Assets use case. To ensure this, data and signals need
to be transported between the different actors which is the focus of Data Transport in both Access
and Wide Area Networks. The main issue with the data transport is that the network used for this
purpose, is not perfect and adds stochastic delays (potentially leads to loss of connectivity) as well as
packet loss to the transport. These undesirable effects are caused by various reasons in the networks
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and lead to different undesirable behaviors causing potential troubles for the control of the system
and therefore affect the Control of Assets case. Therefore it is important to enable the system to
overcome different situations in the communication network. In order to do so, the system must first
be able to detect faults and detect when it is safe to return to normal operational mode. To support
these use cases, there is a range of network activity necessary, first the monitoring of the
communication network is required to keep track of what is going on in the communication network;
second scalable management of data access mechanisms is a necessity to overcome the potential
number of sources and the geographical spread. To support the data access, data quality estimation
is also done. By this estimation process, data collected can be attached quality attribute that are
useful for efficient data access management. This may require reconfiguration of the network or
completely using a different communication network infrastructure. Finally, registration of
communicating entities is needed for the system to be aware of what is interacting with what.
4.2.2 Control of assets
The normal operation defines three sub cases that will be considered in the use case:
Energy balance – where the operation of MV grids is targeted. LV grids are considered aggregated and the LVGC is offering flexibility to the MVGC. Thus the MVCG is primarly controlling the assets such as Large DER, prosumers and LV grid via the LVGC to keep the energy balance. The primary actor involved here is the WAN Provider
MV operation – where the focus is to control the voltage profile as well as to optimize losses and energy costs on MV grids using active and reactive power capabilities offered by Large DER, MV prosumers and the secondary substations on MV side. The primary actor involved here is the WAN Provider
LV control - where the focus is to control the voltage profile on LV grids using reactive power capabilities offered by Micro and Intermediate DER, flexible consumption and production at household or small and medium enterprises. The primary actor involved here is the AN Provider(s)
These subcases may involve only some of the actors while other are neglected as mentioned above.
A detailed description of these scenarios is given in 10 Annex B - UC templates
4.2.3 Network adaptive data transport (AN/WAN)
The data transport covers the communication required to execute normal operations as described in
previous sub section, and generally covers data and signaling between entity A and entity B, and is a
part of the normal operation situation as shown in Figure 18. The use cases for the AN and WAN
focus on adapting the network layer to overcome different performance issues in the network that
affect the operation of the Control of Assets. For the network part, three fault/error cases are
thereafter considered (detailed views on these can be found in Annex B - UC templates):
Network Performance Changed - This scenario deals with time varying performance in the network, and the adaptation of access methods to provide reliable data exchange between entities communicating. This scenario is relevant for both WAN and AN.
Network Congestion - This scenario deals with more severe network conditions, i.e. congestions in the network, and the adaptation of access methods to provide reliable data exchange between entities communicating. This scenario is relevant for both WAN and AN.
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Lost Network Connectivity - This scenario addresses the case where devices loose
connectivity at the network layer. The case assumes a certain notion of connectivity, e.g. as
in TCP. This scenario is relevant for AN only.
4.2.4 Architecture and Sequence Diagrams
In the following a brief overview of the architecture and functionality of the use case diagram is
provided in component and functional layers as described in [UCC]. This approach describes the
relation between components and functions in terms of electrical grid components (x-axis) and zones
of operation (y-axis) which is helpful also to understand the need for communication between the
various components and functions. Following this, a high level message sequence diagram connects
these components and functions in time.
Component Layer
TSO
AN NetworkProvider(s)
MV grid control
RetailerForecast Provider
TechnicalAggregation (LV)
LV grid control
Large DER
DMS
TechnicalAggregation
(MV)
WAN NetworkProvider(s)
Markets
Prosumer Micro DER ConsumerIntermediat
e DERProsumer
Smart Meter
Smart Meter
Smart Meter
Smart Meter
MV Grid Components
LV Grid Components
Station
Distribution DER Customer PremisesTransmission
Field
Process
Operation
Enterprise
MarketWAN Channel(s)
Private Channel(s)
AN Channel(s)
Figure 16 Components distributed in the external grid operation case
This figure illustrates what components are foreseen to be used in order to effectively execute the
use case Control of Assets shown in Figure 15, and although it appears quite wide, the focus in deed
is to balance the energy in the system which requires both MV and LV operations as well as
interaction with the external world related to the market and TSO. The setup in the scenario requires
several different types of DERs for proper energy balancing, with specific focus on the LV side
considering the technical and commercial aggregation as main points of operation. For completeness
to describe and understand the full operation of the grid, MV and some functionality from the LV/MV
and MV/HV is also needed as well as the parts related to commercial operation, e.g. retailers and
market interfaces. Communication will be focused to the Access Network and to some extend also
the Wide Area Network, which poses challenges due to a continously changing condition and
enviornment. Different traffic patterns, link conditions etc. will change the properties of the network
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over time, which needs to be handles. This will be addressed in the Data Transport use cases, and
the challenges as described in the sub cases.
TSO
AN NetworkProvider(s)
MV grid control
RetailerForecast Provider
TechnicalAggregation (LV)
LV grid control
Large DER
DMS
TechnicalAggregation
(MV)
WAN NetworkProvider(s)
Markets
Prosumer Micro DER ConsumerIntermediat
e DERProsumer
Smart Meter
Smart Meter
Smart Meter
Smart Meter
MV Grid Components
LV Grid Components
Station
Distribution DER Customer PremisesTransmission
Field
Process
Operation
Enterprise
Market Market prices
Weather
information
Commercial
aggregation
HV grid management,
GIS system data,
planning tools,
visualisation
MV/LV grid
management, GIS
system data, planning
tools,
visualisation
Technical aggregation
Grid resynch., fault detection and
isolation, demand side mngt and
response, curtailment, ancillery services
Protection and monitoring
Warnings and alarms for
grid failure
Actuation Actuation Actuation
Protection and metering
Functional Layer
Figure 17 Functionalities in the external grid operation case
The functionalities shown in Figure 17 enable the envisioned operation of the Control of Assets use
case. The subsequent message sequence diagram shows an overview of the most important
operation, using the components and functionalities from Figure 16 and Figure 17. The remaining use
cases are found in the annex. At the lowest part, actuation functionality is used to efficiently
distribute actuation messages to the individual assets in the system. Protection metering and
monitoring functionality is running on top of the actuation for efficient and scalable data collection,
and event observation. On the DER side, this also includes some control functionality. On the MV and
LV side there is grid control functionality for the different voltage levels, and for the DER side
technical aggregation that allows the demand-response and production management. Further on
top, functionality for interaction between HV/MV and MV/LV is done, as well as the commercial
aspects are taken into account via functionalities allowing commercial aggregation, market (price)
interaction and interaction with forecast providers, e.g. on the weather situation. Again here,
communication is critical for these functions to perform properly. The impact of the solutions of the
network adaptation found in the Data Transport use cases to changing network conditions; will be
evaluated by the performance of the functions.
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TSOAN NetworkProvider(s)
MV grid controlRetailer
Forecast ProviderTechnical
Aggregation (LV)
LV grid control
Individual setpoints (MV)
Individual setpoints
Large DERMicro DER/
Intermediate DER/Prosumer
Consumer
Measurements
Aggregated flexibility (LV)
Measurements
Aggregated set point
AggregatedFlexibility (LV)
DMS
Weather information
Setpoint
Aggregated flexibility (MV)
Aggregated Setpoint (MV)
Measurements
Measurements
Measurements
NetworkStatus/
performance
Aggregated set point
Individual setpoints
TechnicalAggregation (MV)
AggregatedFlexibility (MV)
Measurements
WAN NetworkProvider(s)
Markets
Price signal
Aggregated setpoint (MV)
NetworkStatus/
performance
Individual
setpoints (MV)
Individual setpoints
Aggregated flexibility (LV)
Individual setpoints (MV)
Measurements
Aggregated flexibility (MV)
Weather information
Bids
Accepted bids
Setpoints
Measurements
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance Figure 18 Overview of the sequence diagram for normal operation mode, capturing Control of Assets and
Data Transport. The specific fault/error cases can be seen in Annex B.
Figure 18 shows the message exchange in normal operation. Starting from the lowest level (right in
the figure), consumers and DERs send measurements to the LV grid controller and receive setpoints
from the LV grid controller. The measurements from LV assets are aggregated before they are sent to
the MV grid controller. Similarly, the LV grid control receives an aggregated setpoint from the MV
grid controller that must be dispatched to the individual LV assets. The MV grid controller
communicates with Large DERs and LV grid controllers to exchange aggregated flexibility,
measurements, and setpoints. Additionally, the MV grid controller sends the aggregated flexibility to
the DMS, which generates setpoints based on the available flexibility, weather information, and
market conditions.
Basically, the operation mode interacts with the different actors as needed, and in particular, the
commercial part interacts also with the market entities to obtain set points for the grid operation.
These steps are continuously repeated with specific time intervals. It is important to realize that the
network use cases are run in the background and effectively evaluates the performance of the
interactions between the entities shown in Figure 18. That is, the overall functionality of the network
is to ensure that the signals shown in Figure 18 are effectively mediated to the different entities
involved. When faults/errors/performance degradation in the network occurs, the smartC2Net
platform shall adapt the strategies such that the overall operation does not necessarily degrades, or
at least to an acceptable level.
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4.3 Automated Meter Reading (AMR) and Customer Energy Management Systems
(CEMS)
This paragraph provides details on the Automated Meter Reading (AMR) and Customer Energy
Management System (CEMS) Use Case.
4.3.1 Objective
The following goals cover the objectives of the user as well as of the operator.
Automated Meter Reading:
Collection of energy consumption data from electric, gas, water and heating metering devices
Transmission of aggregated data from the households to the energy utilities/meter reading operators for billing and accounting
Provide (local) feedback system to the customers in order to provide transparent insight on the current energy consumption and enabling indirect demand side management
Aggregate information of energy consumption in order to balance the distribution grid by enabling direct demand side management
Customer Energy Management Systems:
Improve distribution grid stability by enabling direct demand side management
Reduce energy costs for consumers by shifting flexible loads to less expensive time slots or improve utilization of local energy resources
Optimize the utilization of energy according to supply contracts or other economic targets, e.g. by shifting flexible loads to less expensive time slots
Provide added-value services to the customers
Provide the flexibility information to the Aggregator by gathering customer premises’ data
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4.3.2 Architecture and Sequence Diagrams
Figure 19 helps to get an understanding of the Automated Meter Reading (AMR) and Customer
Energy Management System (CEMS) Use Case (UC) by showing its logical and physical components
(e.g. the physical Network Access Points, not logical information flows) and their locations in the
Smart Grid Setup.
Simple external
consumer display
Home automation end device
Energy Management Gateway (EMG)
Smart Meter (SM)
Customer Energy Management System (CEMS)
Substation Level Operator LevelAutomated Meter Reading (AMR)
Local Network Access Point
(LNAP)
Flexible Loads
Non-Flexible Loads
Metering Operator
Private Charging Spot
Aggregator
Distribution Network Operator
Energy Service Provider
Metering Data Aggregator
Related to EV Use Case
Related to External GenerationUse Case
Related to External GenerationUse Case
Meter Data Management System
Head End System (HES)
Neighborhood Network Access Point (NNAP)
Figure 19 Physical components of the use case and their locations in the Smart Grid setup
The figure depicts how the individual physical components are laid out. The Smart Meters (SM) of
the AMR use case measure the amount of energy, gas and water used in the household. Therefore a
connection between the flexible and non-flexible loads and the Smart Meter is necessary. The SM
interfaces with the Local Network Access Point (LNAP), which provides the WAN connection for
upload of the metering data. It is to be considered that, due to legal restrictions out of privacy
concerns, it is possible that a direct connection between SM and Energy Management Gateway
(EMG) might not exist. An EMG has the ability to controls flexible loads, private parking spots and
home automation devices. The state of these devices, along with current tariff and consumption
information, is made available for the consumer by an external display, which also provides a certain
degree of control over the CEMS. The LNAP has an interface to the Neighborhood Network Access
Point (NNAP) which itself connects to the Head End System (HES) with its subsequent set of devices
and roles. These are the Meter Data Management System (MDMS), Metering Data Aggregator
(MDA), Distribution Network Operator (DSO), Aggregator, Metering Operator and Energy Service
Provider.
Figure 20 delivers a detailed clustering structure of the use case. AMR and CEMS are in the center
and connect to sub use cases with their respective actors.
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DG.01. Direct Load /Generation
management
DG.02. HL-UC Flexibility offerings
DG.03. HL-UC Receiving consumption, price or environmental information for further action by consumer or a local
energy management system
CI.01. Provide Information to
consumer
ES.01. Tamper and Fraud detection
ES.02. Manage supply quality
ES.03. Monitoring
MM.01. Obtain meter reading on demand
MM.02. Obtain scheduled meter
reading
MM.03. Set tariff parameters
Keys
Customerinformation provision AMR Use Cases
<< extends >>
Actor A Actor B Actor C
Demand and Generationflexibility for technical and
commercial operations
Electric Vehicle REF: Use Case Name: Electrical Vehicle
Charging in Low Voltage Grids
Reference to use casedocument
Use Case ClusterUse Case Cluster
Use Case
Actor D
[WGSP Actor B]
[WGSP Actor A]
Collect AMI eventsand status information
<< extends >>
Measurement
Grid related REF: Use Case Name:
External Generation Site and Island Mode
CEMS Use Cases
Figure 20 Detailed use case clustering structure
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The sequence diagrams of the AMR / CEMS use case originate from the CEN-CENELEC-ETSI Smart
Meter Coordination Group and can be found with references in the corresponding use case template
located in the Annex B - UC templates.
Sequence Diagrams Figure Nr. Annex B
CEN Designation
Obtain meter reading on demand 4 MM.01
Obtain remote meter reading on demand 5 MM.01.01
Obtain walk-by meter reading on demand 6 MM.01.02
Obtain scheduled meter reading 7 MM.02
Obtain scheduled meter reading (Sequence Diagram) 8 MM.02.01
Configure reading schedule 9 MM.02.02
Set tariff parameters 10 MM.03
Set tariff parameter in the smart meter 11 MM.03.01
Set tariff parameter in the LNAP/NNAP 12 MM.03.02
Customer information provision 13 Cl.01
Send information to meter display 14 CI.01.01
Send information to simple external consumer display 15 CI.01.02
Smart Meter publishes information on simple external consumer display 16 CI.01.03
Manage supply quality 17 ES.02
Configure power quality parameters to be monitored 18 ES.02.01
Smart meter sends information on power quality to display 19 ES.02.02
Direct load / generation demand – appliance has end-decision about its load adjustment 20 DG.01.01
Direct load / generation demand - appliance has no control over its own load adjustment 21 DG.01.02
Information regarding power consumption / generation of individual appliances 22 DG.03.01
Information regarding total power consumption 23 DG.03.02
Price & environmental information 24 DG.03.03
Warning signals based individual appliances consumption 25 DG.03.04 Table 1 Overview of the CEN-CENELEC-ETSI AMR / CEMS sequence diagrams of Annex B - UC templates
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4.3.3 Fault/threat analysis/scenarios
In this section the possible failures in the CEMS/AMR UC are considered. In particular, the focus is on
security threats that can hamper the CEMS main functionalities since the CEMS may operate in a very
hostile environment. Indeed, the CEMS can be connected to home automation devices and to the
EMG by means of shared network (e.g., the home WiFi, office LAN). The use of already deployed IP
network is extremely appealing since the cost for cabling and network interfaces is rapidly decreasing
[LECH08]. However, IP-based networks, when not well secured, are subject to cyber attacks.
The shift towards such a scenario may expose the communication and the CEMS critical
components, to attacks. For instance, an attacker can be:
a hacker with no intent to cause damage and who is satisfied by the penetration of systems
accessible through the Internet;
a criminal (e.g., disgruntled employee of the Energy Supplier or Energy Service Provider) who
wants to cause financial loss to the customer or to the energy service provider;
a customer with malicious objectives, e.g., to tamper the system with fraud purposes.
The attack can be executed either from the Internet or from a device connected to the HAN which
has been previously tampered, such as a personal computer or the LNAP, and may have special
information or authorizations (e.g., EMG login credentials, remote management of home automation
devices).
All in-house components are assumed to be connected to the CEMS. Among the functionalities of the
CEMS depicted in the use case diagrams (see Figures 20-25), the most critical operations that must
be secured are: i) direct load/generation management (DG.01.01) and ii) communication of power
consumption information (DG.03.01). The considered misuse cases are depicted in Figure 21.
Figure 21 Mis-use diagrams for the considered CEMS functionalities
The alteration or missed delivery of load adjustment commands that can be performed by means of
active attacks, i.e., the attacker tries to alter system resources or affect their operations. This may
compromise the capability of the customer to use the smart appliances or even the execution of
emergency procedures. When the attacker is able to compromise a limited number of CEMS the
impact of the attack is low; however, when the attack is coordinated and several CEMS systems are
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compromised (e.g., more than 100) or when some critical CEMS are violated (e.g., police and fire
departments systems) the impact of the attack can range from moderate to high (e.g., when the
CEMS systems of a very extended area, such as a city, are all compromised in a limited interval of
time). In the following we refer to this misbehaviour as incorrect direct load generation management,
mis-use case DE.01 (see Figure 21). These mis-use cases extend the ones provided by CEN-CENELEC-
ETSI Smart Meter Coordination Group and are fully described in the template located in the Annex B
- UC templates of the deliverable.
The access to power consumption/generation data shall also be secured against non-authorized
accesses. In other words customer power-related data shall be protected against passive attacks, i.e.,
attempts to learn or make us of information from a system without affecting its resources. As a
matter of fact, this is mandatory according to privacy law in some countries of the European
Community, such as Germany. Moreover, sophisticated burglaries could be architected when such
information is not secured. For example, thieves can exploit power consumption data to infer when
persons are not in the buildings and then plan physical penetrations. The impact of such an attack
can be classified as low. In the following we refer to this misbehaviour as disclosure of power
consumption information, DE.02 (see Figure 21).
For the aforementioned motivation, the network security requirements that shall be guaranteed in
CEMS systems are confidentiality, integrity and availability . In particular, for the communication of
direct load/generation management operations (i.e., load and emergency commands) integrity and
availability shall be guaranteed; while confidentiality, integrity and availability shall be assured when
power consumption data are exchanged.
According to the CEMS logical architecture described in Section 1 the most critical components
involved in the aforementioned operations are the EMG and the CEMS. Indeed, these can be
connected to the home WiFi and the likelihood to be exposed to malicious attacks is higher with the
respect to the components that are in dedicated network and when not protected by firewall or
other security mechanisms (e.g., encryption).
Incorrect Direct load and generation management
The considered active attacks that compromise the integrity and/or the availability of EMG/CEMS
and lead to incorrect direct load generation management are:
Man In the Middle (MIM) – an opponent captures messages exchanged between the EMG
and the CEMS. It can partially alter the content of the messages, or the messages are delayed
or reordered to produce an unauthorized effect.
Masquerade – an opponent sends fake messages the EMG pretending to be a different
entity.
Denial of Service (DoS) – the attacker floods anomalous messages to the EMG. It prevents or
inhibits the normal use or management of the communication facilities and/or the
components.
These attacks have been selected since they are usually performed by exploiting the most commonly
computer system and network vulnerabilities (e.g., sensitive data exposure, insecure object
references, broken authentication and session management, security misconfiguration). MIM and
Masquerade attacks can violate both integrity and availability; while, DoS violates only availability.
Tables Scenario D.01.01-D.01.03 and Figure 118-115, which can be located in the AMR / CEMS
template in Annex B - UC templates detail the considered active attack scenarios. It is worth noting
that just one interaction is considered for the mis-use cases DG.01.01 and DG.03.01; in particular, it is
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assumed that the Actor D starts the communication. However, a similar analysis can be applied when
Actor A initiates the communication.
The step by step description of the MIM attack is explained for the sake of clarity. As for other
attacks (i.e., masquerade and DoS) further explanations can be founded in the Annex B.
Figure 22: Mis-sequence diagram for the MIM attack
The MIM attack assumes an adversary can (i) observe messages exchanged, (ii) intercept messages
and (iii) reply messages with altered content (e.g., a load adjustment command sent by the EMG).
The attack takes place when the adversary intercepts the load adjustment command sent by the
EMG. Then, the attacker modifies the message previously intercepted and sends it to the CEMS. The
CEMS is not aware of the adversary modification and takes the load adjustment command as
appropriate and replies to the message. Hence, the attacker intercepts and alters the expected
change message sent by the CEMS (i.e. the reply to the load adjustment command) and finally sends
the altered message to the EMG. In this scenario, it is assumed that the CEMS sends the response
message to the EMG. However, the attacker might also be able to redirect all messages sent by the
CEMS to himself, e.g., by means of DNS tempering.
Disclosure of power consumption information
In this section the focus is on passive attacks that compromise the confidentiality of power
consumption information exchanged between the EMG and the smart appliances. As for the active
attacks that compromise the integrity and availability, similar analyses performed for the mis-use
case DE.01 also apply for the power consumption communication.
The considered passive attacks that compromise confidentiality are:
Release of message content: the opponent tries to eavesdrop transmissions;
Traffic analysis: the opponent observes the pattern of the messages to discover the location
and the identity of the parties involved in the transmissions, and the frequencies and the
length of exchanged messages.
The disclosure of message content scenario is detailed in Table Scenario DE.02.01, which is located in
AMR / CEMS template of the Annex A. When the smart appliance / generator sends information
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regarding consumption to the CEMS, the CEMS aggregates and/or forecasts total consumption and
sends this information to the display and to the EMG. The attacker may intercept the message and if
no cryptography method is used he/she reads the content about power consumption/ generation.
As for the traffic analysis attack the only differences with respect the disclosure of message attack
(depicted in Figure 29 in the AMR / CEMS template) is that we are assuming that the adversary
cannot understand the message. Hence, the opponent needs to intercept several messages in order
to observe the communication pattern and discover relevant information (e.g., location and the
identity of the parties involved in the transmissions).
Mis-sequence Diagrams Figure Nr. Annex B
Man in the middle (MIM) attack Figure 118
Masquerade attack Figure 119
Denial of Service (DoS) attack Figure 120
Disclosure of message attack Figure 121 Table 2: Overview of the mis- sequence diagrams of Annex B - UC templates
4.4 Electrical Vehicle Charging in Low Voltage Grids
EV charging appears in both the Home scenario, where it is coordinated by the Energy Management
Gateway (EMG, see 2.4), and in the public and semi-public scenario below, in which a charging
station coordinates the operation of several charging spots.
4.4.1 Objective
The objectives of the EV charging sub-system, as described by this use-case, are listed below:
Satisfy the charging demands of arriving EVs in such a way that the generated and stored
energy is efficiently used and the grid is not overloaded.
Enable electrical vehicle charging to become a flexible consumption resource that can be
used to balance energy and power resources in the LV grid along with decentralized
production as well as other loads (e.g. households).
Provide a system architecture enabling interoperation between new actors such as charging
station operators (charging aggregator) and their connection to existing actors such as DSOs
and energy providers.
Enable DSOs to monitor state of low voltage grid under EV load conditions
4.4.2 Architecture and Sequence Diagrams
For SmartC2Net it is significant to describe the view of the various ICT network technologies and
operations constraints (Figure 23):
Network 1 – Metering. The metering network is owned by the DSO or a metering infrastructure
operator. It is a network used to collect smart meter data measurements at the last mile. The smart
meter network is usually based on powerline communications, cellular or proprietary wireless
solutions.
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Network 2 – Sub-station network. This network is an internal bus-network in the secondary
substation. It is owned by the DSO and connects equipment in the substation. May be based on
Ethernet.
Network 3 – Public IP Network. The Public IP network represents the open Internet. This is the
easiest platform for third parties to provide their services, such as routing services to EV users, or
weather services. The public IP network can be based on everything from wired xDSL based
technologies to cellular data access.
Network 4 – eCar Communication. This communication is between the charging station and the
electrical vehicle itself. The communication is usually wired and may be running through the charging
cable itself. Information about the state of the car, e.g. state of charge, preferred charging speed,
etc. may be provided through this network.
Network 5 – Private IP Network The private IP network represents a local network infrastructure
utilized by the infrastructure owner to connect local elements. For instance charging spots may be
connected to the charging station through this network. It could be based on PLC or Ethernet.
Network 6 - LV Grid Management Network. The DSO may choose to deploy an own closed
networking architecture used for grid components to communicate. Thus could be to communicate
with inverters, protection devices as well as sensors in the grid.
Network 7 – DSO Network. The DSO network is the network connecting the DSO management and
control systems (e.g. SCADA) towards the secondary sub-station. These networks are usually closed.
They may be based on fibre put out by the DSO as the cables to substations were put in the ground.
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Secondary Substation
DSO
Local LV Grid
ressources (DER)
Private Charging Station
EVprivch
Public Charging Station
Cloud
NW1: Metering
NW2: Sub-station NW
NW3: Public IP Network
NW4: eCar
CommunicationNW4: eCar
Communication
NW5: Private IP Network
NW6: LV Grid Management Network
Private
Charging
SpotEVpubch
Public
Charging
Spot
NW7: DSO Network
Charging
Station
Controller
Public
Smart
Meter
Photovoltaic
Inverter
Battery
Inverter
Private
Smart
Meter
Energy
Management
Gateway
Metering
Head-end
System
Metering
Aggregation
(NNAP)
Low Voltage
Grid Controller
Meter Data
Management
System
Distribution
Management
System
(SCADA)
Information
Services
Market
(Distribution/Transport)
Charging
Station
Routing &
Reservation
Aggregated
Charging
Infrastructure
Management
Figure 23 Networks of the EV use case
To define how these components are foreseen to interact over the provided networks, the use case
has been divided into three primary scenarios (PS) covering different functions and parts of the
system: 1) a charging scenario, 2) an energy and power management scenario, and 3) a market
scenario.
The overview of the interactions is given in Figure 24:
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DSO
Charging
Station
ControllerLow voltage
grid controller
E-mobility
Service
Operator
Charging
Station
Routing &
Reservation
PS2.10
Charging
spot
PS2.6
PS1.8
PS 1.6, PS 1.9
PS1.6, PS1.9
PS 2.4
PS 2.9
DMS
PV Local
Production
Battery
Storage
PS
2.8
PS
2.7
PS1.
1, P
S1.
3
PS
1.2,
PS
1.5
Aggregator & CSO
PS
3.3
MarketPS3.5
PS
2.5
PS3.4
Meter
Meter Aggregation
PS 1.11
PS1.
11
PS
3.6
Aggregated
Charging
Infrastructure
Management
PS1.3
PS1.4, PS1.7
Figure 24 Overview of the interactions between components
The EV charging scenario PS1.* describes the interactions between the EV owner, charging station
for reservation, plug-in, plug-out.
Scenario PS1
Scenario PS1: EV Charging
Step
No.
Event Name of
Process/
Activity
Description of
Process/Activity
Information
Producer
(Actor)
Information
Receiver
(Actor)
Information Exchanged
PS1.1 Charging
Station
Lookup
Find Charging
Station
Identify charging
station and
provide user
context
(expected stay
duration, needed
charge, …)
EV Owner
+ EV
Charging
Station
Routing
Charging Context.
PS1.2 Availability
Check
Availability
Check and
Response
The Charging
Station
Infrastructure
Mgmt. identifies
charging station
options and
informs EV
Owner.
Charging
Station
Routing
EV Owner Available charging
opportunities.
PS1.3 Reservatio
n
Charging
Station
Routing
receives
reservation
EV user selects
charging station,
arrival time
energy demand.
May get
EV Owner
+ EV
Charging
Station
Controller
Reserve message
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request and
redirects it to
CSO
additional
information such
as routing advice.
PS1.4 Process
Reservatio
n
Reservation
handling at the
charging
station
Update Schedule,
allocate
resources
Charging
Station
Controller
Charging
station
Routing
Schedule update and
resource availability
PS1.5 Reservatio
n
successful
CSO returns
OK
OK response.
Charging station
Routing updates
its CS availability
list
Charging
Station
Controller
EV Owner Reservation
confirmation
PS1.6 Plugin EV Plugin An EV plugs into
the Charging Spot
and provides
additional/updat
ed context
information
EV Charging
Station
Controller/
Gateway
Updated Charging
Context.
PS1.7 Plugin
Handling
Re-planning of
resources
The Charging
Station Controller
(re-)/plans the (if
needed) charging
plan
Charging
Station
Controller
Charging
Station
Routing
Schedule update and
Resource availability
PS1.8 Start/Stop
Charging,
Change
Charging
Speed
Charging
Process
Management
The charging
station controller
starts/stops
charging as well
as manages
charging speed
Charging
Station
Controller
EV Start/Stop commands.
Updated charging
speeds.
PS1.9 Plug-out EV Plugout The EV plugs out
of the Charging
Spot. The
Charging Station
Controller
adapts.
EV Charging
Station
Controller
Plug-out event
PS1.1
0
Periodic Metering Send charging
metering data to
meter
aggregation
system for billing
purposes
Smart
Meter
Meter
aggregatio
n
Meter data
PS
1.11
Periodic Metering Read meters for
state estimation
Meter
Aggregatio
n
LVGC Relevant Meter Data
The PS2.* Scenario relates to the energy balancing and power management at the LV grid level
Scenario PS2
Scenario PS2: Energy Balancing& Power Management
Ste
p
Event Name of
Process/Acti
Description of
Process/Activity
Information
Producer
Information
Receiver
Information
Exchanged
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No. vity (Actor) (Actor)
PS2.0
1
Update
LVGC
operation
Provide
update of
the LVGC
operation
settings
The DMS provides
information to the
LVGC to update high-
level operation
objectives as well as
changes in data
models such as grid
topology information,
newly connected
charging stations etc.
DMS LVGC - Setpoints
- Settings
- Data models
(e.g. grid
topology)
PS2.0
2
Update
LVGC
prediction
informatio
n
Provide
update of
the LVGC
data for
prediction
Information is pushed
(or pulled) from
information services
that are useful in the
LV grid management
operation such as
weather data.
Information
Services
LVGC - Weather
data
- Expected
load profiles
- …
PS2.1 Periodic Load and
Production
Prediction
The LVGC predicts the
expected production
and load a predefined
time into the future
for planning purposes
LVGC LVGC Updated
prediction
profiles
PS2.2 Periodic Metering Current load in
different busses of
the LV grid
Metering
Aggregation
LVGC Load
information
on busses
PS2.3 Periodic Distributed
Generation
Current generated
power in different
busses of the LV grid
Metering
Aggregation
LVGC Generated
information
on busses
PS2.4 Periodic Set Available power
for EV charging to all
charging stations
LVGC Charging
Station
controller
Available
power profile
PS2.5 Periodic Control
Re-planning
The LVGC plans the
local power and
energy resources to
maintain service
quality within
acceptable limits. It
may perform this
planning based on
setpoints from the
MV level.
LVGC LVGC Power and
Energy
control plan in
the LV grid.
PS2.6 Periodic Charging
Load profile
update
CSO updates the
schedule considering
the preferred loads
from aggregator and
the CSO available
power constraints
Charging
Station
Controller
LVGC EV Loads
update
PS2.7 Overvolta
ge/Curren
t
Limit
Production
If overvoltage/
over-current events
occur the LVGC can
choose to limit the
production in critical
periods to maintain
LVGC Photovoltai
c Inverter
Production
Limits
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power quality.
PS2.8 Service
quality
deviations
Change
battery
control
objectives
A local battery in the
grid can be requested
to change its
objectives to
increase/decrease
load to aid in the
operational
parameters
LVGC Battery
Inverter
Setpoints/obj
ectives for
battery
control
PS2.9 Power
quality
deviations
Change
demand
objectives
The LVGC can request
flexibility services
from the Charging
Station Controller to
increase/decrease
load now and in the
future. This involves
hard constraints on
power availability.
LVGC Charging
Station
Controller
Setpoints/obj
ectives for
-charging
demand
flexibility
- Available
power profile
PS2.1
0
Events/Al
arms
Monitoring
events/Alar
ms
A monitoring event or
alarm (depending on
criticality level) is
raised and sent to the
DMS to report about
the current and past
state of the LV grid.
LVGC DMS Event/Alarm
Scenario PS3 adds the view of EV aggregator/Utility
Scenario (see Figure 80 & Figure 81)
Scenario: PS3: Energy Market
Step
No.
Event Name of
Process/Activi
ty
Description of
Process/Activity
Information
Producer
(Actor)
Information
Receiver
(Actor)
Information
Exchanged
PS3.1 Periodic Sell
Production
Local energy sources
(storage and production)
sell energy resources to
an aggregator.
DER/Battery
owner
Aggregator Energy
production
capabilities
PS3.2 Periodic Sell
Aggregated
Production
Local energy resources
across several LV/MV
grids are aggregated
enabling the aggregator
to act on the retail
market
Aggregator Market Aggregated
energy
production
capabilities
PS3.3 Periodic Provide
EV charging
demand
The charging station
forwards an already price
optimized demand curve.
(alternatively, it forwards
the demand plus its
flexibility and the
aggregator performs the
price optimization)
CSO EV
Aggregator
(retailer)
demand +
flexibility
capabilities
PS3.4 Periodic Price signals pricing information is
provided to energy
providers/aggregators.
Market EV
Aggregator
Price signals
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PS3.6 Periodic Price signals The CSO uses the price
information and the
flexibility of the charging
operation to find an
optimal demand curve
EV Aggregator CSO Price
signals
PS3.5 Periodic Price
Optimized
Energy buying
The aggregator buys
updates the energy need
by buying on the intraday
market
EV Aggregator Market Demand
4.4.3 Fault/threat analysis/scenarios
The fault/anomaly scenarios AS1 and AS1 address network interruptions: AS1- the connection
between LVGC and a charging station and AS2 – the connection between meters and LVGC is
interrupted.
Scenario
Scenario (Sub-
scenario)
AS1: EV demand control disrupted
Step
No.
Event Name of
Process/Activity
Description of
Process/Activity
Information
Producer
Information
Receiver
Information
Exchanged
AS1.1 LVGC CS
connection
lost
Scheduling under
av. power
uncertainty
Enter precautious
mode. Refuse new
requests
CSO Charging
Spots
reduced
charging
duration
Scenario
Scenario (Sub-
scenario)
AS2: Metering data flow disrupted
Step
No.
Event Name of
Process/Activ
ity
Description of
Process/Activit
y
Informati
on
Producer
Information
Receiver
Information Exchanged
AS2.1 consumption
Metering
samples
missing
Estimate
load under
uncertainity
Conservative
calculation of
available
power
LVGC CS
controller
Reduced Available
power
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5 UC ICT requirements & success KPI
In any system development process the requirements represent the definition of the system
functions and their desired properties. As such the identification of UC requirements has been
considered as mandatory to the further development of the SmartC2Net UC.
In addition to UC requirements a list of Key Performance Indicators (KPI) has also been provided in
this initial phase as supporting the next development and evaluation activities of the SmartC2Net
components.
The requirements and the KPIs are determined from the use case analysis and they are studied under
several perspectives in order to identify those mostly related to the SmartC2Net objectives. Their
mapping with the SmartC2Net WPs allows understanding how the project developments will be
addressed and evaluated.
For the collection of the requirements and KPIs two templates have been used. For sake of simplicity
and readability the revised version of the requirement and KPI tables are collected in Annex C - Table
of Requirements and Annex D - Table of KPIs. In the next sections the respective templates are
presented first, followed by the relevance indications elaborated from the tables.
5.1 Requirement Template
Each requirement is characterized by several fields which both identify and characterize it. The
description of the characterization field is reported in Table 3:
Field Value Description
Requirement ID REQ_<nnn> This field contains a unique identifier of the requirement where <nnn> is a unique sequential number which identifies the requirement
Level This field specifies the logical level where the requirement is allocated. A requirement can be a general one specified for the whole system or a specific one for an individual component
SYS Whole system oriented
UC Use Case oriented
CO Individual component oriented
Priority This field specifies whether the requirement is considered for being created right now, or is a future development or is desirable
N Now: the requirement is taken into serious consideration inside the project
F Future: to be considered at some point in time
W Wish: the requirement is considered desirable but not yet scheduled in the project activities
UC Name This field specifies the reference UC if applicable
Title This field reports a brief description of the requirement
Category This field specifies the category of the requirements. For example if the requirement specifies a functionality or is dictated by standards.
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Field Value Description
Functional This category comprises requirements about the functionality of the system/component including technical constraints such as:
voltage ranges
active/reactive power ranges/limits
generation/load coefficients
sample rates
EV schedule time horizon/resolution
generation/load profile time horizon/resolution
Architectural This category comprises architectural requirements
Dependability this category contains requirements about
Availability: readiness for correct service
Reliability: continuity of correct service
Integrity: absence of improper system alterations
Maintainability: Ability to undergo modifications and repairs
Security This category is a composite of the attributes of:
Availability for authorized actions only (access control, authorization, deny of service)
Confidentiality: absence of unauthorized disclosure of information
Integrity: data integrity, non-repudiation
Performance (Quality of Service)
This category comprises some specific performance requirements including the following time constraints: refresh time, response time, actuation time
Interface This category comprises interface requirements.
Communication This category comprises the requirement about the communication infrastructure including the following subcategories:
Communication size: possible measures are: bandwidth, data rate, range (Km), frequency band
Communication performance: possible measures are: delay, overhead
Communication availability: possible measures are sec-min-hour/year
Communication security: possible measures are # lost packets/messages, # discarded packets/messages, # faked messages
Communication cost: possible measures are €/y per connection point
Environment This category comprises requirements about the operational environment in which the system shall work.
Standard/Regulation This category comprises requirements dictated by the standards.
Description The description of the requirement
Table 3 Requirements Template Description
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5.2 Requirement analysis
Requirements represent an essential step in order to understand what the specific necessities of the
different use cases are. These functional and technical properties will drive the developments in the
other WPs. In particular these requirements will be used as inputs for the adaptive monitoring
(WP2), for addressing the adaptive communication (WP3), for the grid control algorithms (WP4), for
the validation of the models in WP5 and for the testbeds developed in WP6. In the requirement
study the mapping between the specific item and the related project WP is presented and some
analysis proposed.
Figure 25 provides an overview of the distribution of the four use case requirements over the
different project WPs.
Figure 25 Requirements: Project WP mapping
WP5 and WP6 (modelling and experimental analysis) are the most represented because the major
part of the requirements offers input for the evaluation work packages. In particular Figure 26
displays the mapping with the Monitoring, Communication and Control WP and Figure 27 shows
as the requirements are subdivided according to the model or testbed analysis.
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Figure 26 Requirements: WP2, WP3 and WP4 mapping Figure 27 Requirements: WP5 and WP6 mapping
These requirements are obtained considering different aspects as functionality, performance
(availability, latency...), maintainability (monitoring), and security (protection, authentication,
authorization …). Detailed lists of requirements tend to be extensive. In this section an analysis of the
requirements annexed in Annex C - Table of Requirements is presented. The whole set of
requirements is composed by a total of 136 items.
The subdivision considering the different use cases is depicted in Figure 28. The Medium Voltage
Control use case includes 46 requirements, the Electric Vehicle in Low voltage use case includes 22
requirements, the External Generation Site use case includes 26 requirements and the AMR/CEMS
use case includes 42 requirements.
Figure 28 Requirements: Use Case
Figure 29 shows the distribution of the requirements considering the different categories: Functional,
Communication, Interface and Security are the most represented as can be inferred by the scope of
SmartC2Net project.
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Figure 29 Requirements: Category
Another index/view that can be considered by the requirement analysis is the Level field, whose
graph is represented in Figure 30. More than half of the total requirements are of system level.
Figure 30 Requirements: Level
The list of requirements comprises a large number of items, it is important to highlight which of them
are more relevant for the project development. In order to obtain this indication it is possible to
analyse the priority field assigned to each requirements. Figure 31 shows the distribution of the
priorities and it is possible to note that the main part is tagged as “N” (now). This means that these
requirements are currently addressed.
Figure 31 Requirements: Priority
In the following pictures (Figure 32 - Figure 39) the graphs corresponding to UC specific
requirements are presented. From a first look, it can be observed that some UC, e.g. the EGS, only
included a subset of the template categories/levels. This means that those requirements have been
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identified as relevant to the SmartC2Net objectives, and it has not to be interpreted as a restriction
of the type of smart grid application that the UC is representing.
Figure 32 MVC UC Requirements: Category Figure 33 MVC UC Requirements: Level
Figure 34 EV UC Requirements: Category Figure 35 EV UC Requirements: Level
Figure 36 EGS UC Requirements: Category Figure 37 EGS UC Requirements: Level
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Figure 38 CEMS AMR UC Requirements: Category Figure 39 CEMS AMR UC Requirements: Level
The UC developments in the next phases of the project will allow refining the current list of UC
requirements in the Annex C.
5.3 KPI Template
As for the requirements, also for the KPIs a template is introduced. In Table 4 the fields involved and
their brief description are provided.
Field Value Description
KPI_id KPI_<nnn> This field contains a unique identification number of the KPI where <nnn> is a unique sequential number which identifies the KPI
UC text UC reference
KPI name text Name of the KPI
Description text A brief description
Category
This field specifies the category of the KPI, for example if it is a technical ,or social or economic KPI
Technical_Power KPI related to technical power aspects
Technical_Communication KPI related to technical communication aspects
Social KPI related to social aspects
Economical KPI related to economic aspects
General General KPI
Scope
This field specifies the scope of the KPI, in terms of the main entities involved
Customer Customer oriented
DSO DSO oriented
CSO Charging Station Operator oriented
Aggregator Aggregator oriented
CSP Communication Service Provider oriented
Goal Expectation, objective Table 4 KPIs Template Description
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5.4 Key Performance Indicators (KPIs) analysis
The Key Performance Indicators (KPIs) represent a way to identify the important values to take into
account for the evaluation of the success of a proposed solution. Accordingly, choosing the right KPIs
relies upon a good understanding of what is important for the use case in relation to the SmartC2Net
objectives. The KPIs will be used in the others WPs, in particular in WP2 for the analysis of the
monitoring solutions, in WP3 for the validation of the communication architecture approaches
defined and in WP4 for estimate if the control techniques developed are satisfactory. Also the
assessment framework developed in WP5 and testbed implementation in WP6 take into account the
KPIs in order to evaluate the technologies and algorithms considered in the project.
Figure 40 shows the mapping of the KPI listed in the Annex D with the different project WP: we see as the identified KPIs will be used in order to validate the model and testbed implementation. The main WPs involved are the model related WP (WP5) and the testbed WP (WP6).
Figure 40 KPIs: Project WP mapping
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WP5 and WP6 (model and testbed work packages) implement the solutions developed in WP2, WP3 and WP4. All the KPIs addressed by Monitoring (WP2), Communication (WP3) and Control (WP4) WPs are also addressed by one or both the model (WP5) and testbed (WP6) WPs. For this reason a more interesting analysis is presented in Figure 41 where we see as the Monitoring (WP2), Communication (WP3) and Control (WP4) related KPIs are subdivided and in Figure 42 as these KPIs are evaluated by means of model (WP5) and testbed (WP6) analysis. The ICT related KPIs are relevant for the SmartC2Net project: they are spread over the different WPs. The KPIs important for some aspect of smart grid, but not for the scope of the SmartC2Net project are not addressed by any WP.
Figure 41 WP2, WP3 and WP4 mapping Figure 42 WP5 and WP6 mapping
In the following we focus the KPI analysis considering the four use cases. The KPI complete list is
presented in the Annex D. In the progress of the project they will be refined and those KPIs that will
be common to all UCs will be identified as global or smart grid level KPIs.
Figure 43 KPIs: Use Case
A total of 68 KPIs are identified and Figure 43 plots their distribution per use case.
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Figure 44 KPIs: Scope
If the scope field is selected as the analysis index, in Figure 44 it is possible to notice that the major
part of KPIs is DSO oriented. This is not surprising, as many UC objectives are related to the
optimization from the utility perspective.
Figure 45 KPIs: Category
Another interesting field that can be considered is the category: in Figure 45 it is possible to see as
the main categories are the technical ones. In particular as we can suppose, the power and
communication categories are the most represented.
In the following pictures (Figure 46 - Figure 53) the specific use case graphs are presented showing
the UC specific focus.
Figure 46 MVC UC KPIs: Category Figure 47 MVC UC KPIs: Scope
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Figure 48 EV UC KPIs: Scope Figure 49 EV UC KPIs: Category
Figure 50 EGS UC KPIs: Scope Figure 51 EGS UC KPIs: Category
Figure 52 CEMS AMR UC KPIs: Scope Figure 53 CEMS AMR UC KPIs: Category
6 Preliminary overall architecture
Starting from a bottom-up analysis of the individual use case architectures a preliminary high level
architecture is derived at the aim of highlighting the interactions among the respective control
components and ICT networks. This integrated view allows having a comprehensive picture of the ICT
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aspects addressed by the SmartC2Net project. It is important to have not only the specific use case
view, but also a global outlook in order to understand what are the common aspects and interactions
as well as the parts of architecture that the different use cases share.
This preliminary version of the overall architecture is aimed at defining the logical interfaces of the
different control components. Where alternative architectures might be envisioned for a specific use
case, e.g. for the Home Energy Management UC, we decided to include all the alternatives to cover in
the overall architecture as many case instances as possible.
6.1 Global architecture
One of the main targets of the SmartC2Net project is to demonstrate that it is feasible to have a
robust control of the power grid using and open and heterogeneous communication infrastructure.
In fact, while at the Generation and Transmission areas, the communication infrastructures are
normally private and protected from external access, the Smart Grid extends the areas where the
communication between devices is required to the medium and low voltage areas, which were, till
now, unobserved and uncontrolled. The proposed preliminary architecture aims at satisfying the
requirements of power grid monitoring, communication network monitoring and grid control
associated with the Use Cases and that will be developed in WPs 2, 3 and 4. This architecture may
nevertheless be further tuned during the project evolution.
6.1.1 Layered architecture
The proposed architecture maps the architecture of the Distribution System, by having components
in the different sites that can be found in a typical electrical distribution grid.
Different areas are involved: there are equipment and systems located at the Central Management
Level, at the Primary Substations, at the Secondary Substations and at the Customer Premises.
In particular the Distribution Management System (SCADA/DMS) and the Demand Response System
are placed at the Central Management Level. Since they have a view of the entire power grid and
communication network, their actions may have a global scope.
The Medium Voltage Grid Controller (MVGC) is located at the Primary Substation (HV/MV). Its
actions will have a local scope, interacting with the Primary Substation and with other systems
connected to it, namely DERs (MV) and Secondary Substations.
The Low Voltage Grid Controller (LVGC) is located at the Secondary Substation (MV/LV). Its actions
will also have a local scope, with low voltage devices and systems, connected to the Secondary
Substation, namely Customer Installations and DERs (LV).
At the Customer Premises several equipment and systems are placed: Smart Meter, Customer Energy
Management System, PV inverter, EV Charger, flexible and non-flexible loads.
Other systems outside the Distribution Grid will also be taken into consideration, namely the Energy
Management System, owned by the TSO, Weather Forecast Information, Market Operators, EV
Charging Operators, Telecom Operators Information Systems and third party Aggregators.
Equipment and systems that may exist in the Distribution Grid but that may not be owned by the
DSO, like Distributed Energy Resources (Distributed Generation, Flexible Loads) are also considered.
The following figure shows the different sites, equipment and systems as well as the communication
networks that connect them.
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Figure 54 Overview of the SG architecture
6.1.2 Distribution of functions
The proposed architecture also allows the distribution of functions across several locations and
equipment, allowing the processing of data close to the data sources and data users.
At the Central Systems Level the following functions will be implemented:
Global Grid Monitoring
Global Grid Management
Global Communications Network Monitoring
Global Communications Network Management
Demand Response
At the Primary Substations the following functions will be implemented:
Distribution Grid Monitoring
Distribution Grid Management
Communications Network Monitoring
Communications Network Management
Distributed Energy Resources (DER) control (MV)
At the Secondary Substations the following functions will be implemented:
Distribution Grid Monitoring
Communications Network Monitoring
Demand Response
Load Management
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Distributed Energy Resources (DER) control (LV)
At the Customer Premises the following functions will be implemented:
Load Management
Micro generation Management
EV Charging
Some functions may extend a single location and will be distributed across several sites. The EV
Charging Use Case is an example of such a situation.
6.2 Use Case mapping
The following sections describe how the proposed architecture maps the chosen use cases.
In order to provide a global vision of the infrastructure and not only restricted to the single use case,
the following figures show how the different Use Cases and the different equipment, systems and
communication networks are related.
Figure 55 gives a general view of the Use Cases and the equipment, systems and communication
networks that are going to be involved in each of the Use Cases.
The figure shows for each use case, which sites and which equipment and systems are involved.
External systems are also shown.
It can be seen that the Use Cases are not isolated from each other and more than one Use Case
involves the same sites and the same equipment, systems and communication networks, sharing a
common architecture.
It can be seen in the figure that the Medium Voltage Grid Controller, DER (MV) and Flexible Loads are
involved in the Medium Voltage Control and the External Generation Site Use Cases.
Also the Low Voltage Grid Controller and several equipment and systems located at the Customer
Premises are involved the External Generation Site, Electrical Vehicle Charging and Customer Energy
Management System and Automated Meter Reading Use Cases.
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MVG
DER
WAN
DMS - Distribution Management
System
DSO Center
Primary Substation
WANFlexible
Load
LVGSecondary Substation
AN
Customer
Charging StationCEMS
MVC UC
CEMS & AMR UC EVC UC
External Generation Site UC
External Systems
Information Service
Aggregation Controller
Charging Station &Routing Reservation
Weather forecast
Distribution Market
Legend:DSO: Distribution System OperatorWAN: Wide Area NetworkMVG: Medium Voltage GridDER: Distributed Energy ResourceAN: Access NetworkLVG: Low Voltage GridUC: Use CaseMVC: Medium Voltage ControlCEMS: Customer Energy Management SystemAMR: Automated Meter ReadingEVC: Electrical Vechicle Charging
Figure 55 Overview of Use Cases mapping
Figure 56 provides a detailed view of the system architecture, mapping all the involved equipment
and systems, either directly associated with the distribution grid or external, and also the
communication links that connect them. In particular the Logical Interfaces (LI) are represented.
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Flexible Load Control
Charging Spot
Charging Spot
EV
EV
Private Charging Station
Public Charging Station
Local LV grid resources (DER)
DSO Operation Center
Primary Substation
Substation Automation System
Capacitor Bank OLTC
DER(generic)
Flexible Load(generic)
Load Forecast
TSO
GenerationForecast
Weather Forecast
MVC UC
Micro-combinedHeat and power unit (Micro-CHP)
Simple externalConsumer display
Photovoltaics
Smart Meter
AMR
Metering Aggregation(NNAP)
Home automationend device
MV/LV Secondary Substation
HV/MV Primary Substation
Central Management
DER Control
Non flexible load Flexible LoadDER
AN
Customer
Photovoltaic Inverter
Battery Inverter
EVC UC
CEMS & AMR UC
External Generation Site
UC
LI1: Internal Communication
LI2: TSO Communication
LI3: Control communication between Control Center and primary and secondary substation
LI4: Metering communication
LI5: Control communication inside LVG
LI6: Local control communication
LI7: Control communication inside MVG
LI8: Communication between External System and SmartC2Net
Metering Head-endSystem (HES)
Charging StationController
PublicSmart Meter
DSO Enterprise Center
TSO: Transmission System OperatorDSO: Distribution System OperatorWAN: Wide Area NetworkMVG: Medium Voltage GridDER: Distributed Energy ResourceAN: Access NetworkLVG: Low Voltage GridUC: Use CaseMVC: Medium Voltage ControlCEMS: Customer Energy Management SystemAMR: Automated Meter ReadingEVC: Electrical Vechicle ChargingOLTC: On Load Tap ChangerNNAP: Neighborhood Network Access Point
MVGC
External Systems
Legend
Low Voltage Grid Controller
EMG
PrivateSmart Meter
Charging Station &Routing Reservation
Information Service
LI_DMS_TSO
DMS
Aggregator Controller
Energy Storage
UPS
Wind Turbines/plants
Refrigerator System
Demand/Response ManagementControl
Tariff Management
EV Charging Station
Secondary Substation
LI_Weather_LoadForecast
LI_DMS_LoadForecast
LI_DMS_DMC
LI_DMS_GenForecast
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Management System
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LI_MVGC_DER (generic)
LI_MVGC_FlexLoad
LI_MVGC_EVCS
LI_MVGC_Ref
LI_LVGC_PVInv
LI_LVGC_BatteryInv
LI_LVGC_CSC
LI_P
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v_B
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_CS
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LI_DMS_GridDBDistribution Market
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LI_CSC_AggContr LI_EMG_AggContr
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External Systems
Aggregator Site(can be included with DSO/TSO)
Wind Turbine(s)
LI_SM_WT
Flexible Load
LI_A
MR
_CS
LI_PrSM_CS
Figure 56 Detailed view of Use Cases mapping
In the Medium Voltage Control use case, the SCADA/DMS, located at the Central Systems Level
communicates with the Medium Voltage Grid Controller located at the Primary Substation through
the logical interface LI_DMS_MVGC in Figure 56. To interact with the Primary Substation equipment,
communication between the Medium Voltage Grid Controller and the Substation Automation System
will be required (logical interface LI_MVGC_SAS).
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In order to perform the voltage control, the Medium Voltage Grid Controller needs to receive
measurements from and send setpoints to DER (MV) and Flexible loads. This exchange of data is
performed using the logical interfaces of type LI7.
Communications of the SCADA/DMS with external systems will also be required, namely
communications with the Energy Management System owned by the TSO (logical interface
LI_DMS_TSO), the Weather/Load Forecast Systems and Aggregator (logical interfaces
LI_DMS_GenForecast and LI_DMS_LoadForecast).
In the Electrical Vehicle Charging use case, the SCADA/DMS, located at the Central Systems Level, the
Low Voltage Grid Controller located at the Secondary Substation and the EV Charger, Smart Meter
and Micro-generation located at the Customer Premises will be involved.
Communication with external systems, namely Market Operators, Charging Station Operators and
Routing Reservation systems will be required.
In Public Charging Stations, the Charging Station Controller will also be involved.
n the External Generation Site use case, the SCADA/DMS and the Demand Response System, located
at the Central Systems Level, the Low Voltage Grid Controller located at the Secondary Substation
and the flexible loads and Micro-generation located at the Customer Premises will be involved.
DER (Distributed Generation and Flexible Loads) connected to the Medium Voltage Grid will also be
considered.
In the Automated Meter Reading and Home Energy Management use case, the SCADA/DMS, located
at the Central Systems Level, the Low Voltage Grid Controller located at the Secondary Substation
and the Home Energy Management System and Smart Meter located at the Customer Premises will
be involved.
Other devices like flexible loads, Micro-generation (PV inverters, Micro-CHP), EV chargers, in-Home
Automation devices, Consumer Display, will also be considered. The Aggregator, the Metering Head-
end System and an EV charging spot are also involved in providing the functionality of the
AMR/CEMS UC.
This first sketch of the high level architecture provides a view of each smart grid application
integrated in the global smart grid control, highlighting the main logical component interfaces. This
overall architecture has to be considered as preliminary and will be updated at the end of Year 2
according to the progress of WPs 2-5 and to the lab prototype setup in WP6. Starting from this
preliminary overview architecture the other WPs take inputs for monitoring, control and
communication aspects. Also the development of the System Assessment and the Test Beds need
information obtained from this architecture.
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7 Conclusions and Outlook
This deliverable includes the control scenarios analyzed in SmartC2Net and provides many
information about their ICT architectures. In particular four use cases representative of the Smart
Grid domain are described and critical anomalous scenarios related to faults and threats identified.
From the energy market model the business driver and requirements associated with the use cases
are analysed, allowing to compare the possible technological and architectural options in the use
case over their benefits and their architecture impacts.
A first sketch of the high level architecture is presented with the specific aim of developing a view of
each smart grid application integrated in the global smart grid control, highlighting the main logical
component interfaces. However the overall architecture has to be considered as preliminary at this
project phase and to be updated at the end of Year 2 according to the progress of WPs 2-5 and to the
lab prototype setup in WP6.
The outcome from the UC analysis and the overall architecture have provided inputs to all the other
project WPs, defining the requirements and the architecture border for the development of the
Adaptive Monitoring (WP2),the Adaptive Communication Solution (WP3), the Adaptive Control
(WP4), the System Assessment (WP5) and the Test Beds (WP6) that will focus on the UC
requirements. Some fault and attack scenarios identified by the UC analysis will be modeled in the
System Assessment (WP5) and implemented in the Experimental Prototypes (WP6), where the
impact of the use case integration in the overall architecture on the grid operation will be analyzed
from a technical stand point. In the last phase of the project the output of the economic analysis will
be re-considered in the exploitation task (WP7) to define the business impact of the SmartC2Net
solutions.
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8 Bibliography
[ADL12] Arthur D. Little: Telco and Utility: Friend or Foe?, Energy & Utilities Viewpoint, 2012. Web access: http://www.adlittle.com/downloads/tx_adlreports/ADL_ENRUTL_2012_TelcoUtility_Friend-or-Foe.pdfWeb access: http://www.adlittle.com/downloads/tx_adlreports/ADL_ENRUTL_2012_TelcoUtility_Friend-or-Foe.pdf
[AFSP07] L’Abbate, A., Fulli, G., Starr, F., & Peteves, S. D. (2007). Distributed Power Generation
in Europe: technical issues for further integration. Joint Research Center Institute for Energy. WWW. CaRBoNWaRRooM. CoM2007.
[ANME12] Analysis Mason: Case study: Telenor Connexion’s approach to an M2M smart grid
implementation in the UK; May 2012; Steve Hilton
[BDCN12] C Baldi, G Di Lembo, F Corti, F Nebiacolombo, “Monitoring and Control of Active
Distribution Grid” ”. CIRED 2012 Lisbona (PT), 29-30 May 2012
[DoW] SmartC2Net – Description of Work
[DGPT12] G. Dondossola, F. Garrone, G. Proserpio, C. Tornelli, 2012, “Impact of DER integration on the cyber security of SCADA systems – the Medium Voltage regulation case study”. CIRED 2012 Lisbona (PT), 29-30 May 2012
[EPRI10 ] M. Wakefield: Methodological Approach for Estimating the Benefits and Costs of Smart
Grid Demonstration Projects. Electric Power Research Institute (EPRI), 2010. [FIER11] FierceSmartGrid: Telecom's evolving role in smart grid 2011. Web Access:
http://www.fiercesmartgrid.com/story/telecoms-evolving-role-smart-grid/2011-04-20
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[FIEX12] Financial Express: M2M device connections in automotive sector to rise to 277m in
2020. 2013. Web access: http://www.thefinancialexpress-bd.com/print.php?ref=MjBfMDNfMDVfMTNfMV84OV8xNjIwOTg
[FSS12] SGCG/M490/B_Smart Grid Report First set of Standards Version 2.0 Nov 16th 2012 [HaSn89] Hakansson, H., Snehota, I.: No Business is an Island: The Network Concept of Business
Strategy. Scandinavian Journal of Management (1989) 187–200
[IEC104] IEC TC57 IEC 60870-5-104 International Standard
[IEC61850] IEC TC57 IEC 61850(-7-420) International Standard
[IEC 62351] IEC TC57 IEC 62351 International Standard
[IEC TC8] Use Case Approach Part 2 - Definition of Use Case Template, Actor list and Requirement List for Energy Systems – NWIP 8/1307/NP 20 June 2012
[INFO12] Informa: M2M Communications - Turn Potential into Profit. 2012. Web Access:
http://www.informatandm.com/wp-content/uploads/2012/04/M2M-Communications.pdf
[INT12] InTech: Wired vs. wireless in utility markets. Web Access http://www.isa.org/InTechTemplate.cfm?template=/ContentManagement/ContentDisplay.cfm&ContentID=89205
[LECH08] D. Lechner, W. Granzer, and W. Kastner. Security for KNXnet/IP. In Konnex Scientific
Conference, November 2008 [NoRa94] Normann, R., Ramirez, R.: Designing Interactive Strategy: From the Value Chain to the
Value Constellation. John Wiley & Sons (1994) [NTS12] National Technical System – Advanced Technologies: Wired vs wireless in utility
markets, Web access http://smartgrid.testing-blog.com/2012/04/15/wired-vs-wireless-in-utility-markets/
[Petroni12] Petroni P., Smart Grids Operation, automation and protection issues CIRED 2012
Lisbon (Portugal) 29-30 May 2012 [ScTa12] Schleicher-Tappeser, R.: The Smart Grids Debate in Europe. SEFEP working paper,
2012. Web access: http://www.sefep.eu/activities/publications-1/SEFEP-SmartGrids_EU.pdf
[SG-CG/IS 12] CEN-CENELEC-ETSI Smart Grid Coordination Group Smart Grid Information Security
2012 [UC200] SGSP Working Group Use Case WGSP-0200
[UCC] SGCG/M490/E_Smart Grid Use Case Management Process — Use Case Collection, Management, Repository, Analysis and Harmonization
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9 Annex A - Value Networks
Based on the SmartC2Net use case description (see Section 4) two Value Network (VN) models are
created and presented in this section: a generic classical grid and new SmartC2Net / Smart Grid
model. In lieu of value chains (activity chains) or business models (intra-firm concept), VNs are
capable of expressing (non-sequential) value streams in an inter-firm context, also see [HaSn89] and
[NoRa94|.
Thus, the specified VNs aim at capturing relevant entities, i.e., actor roles, from a business
perspective. In this way, technical processes or systems are eliminated from this perspective.
9.1 Electrical Grid Value Network
In order to be able to extrapolate economic differences between the “classical view” on electrical
grids and on the smart grid presented by SmartC2Net, the VN of “classical” electrical grids will
subsequently be briefly revisited by means of its entities and main value flows, and illustrated in
Figure 57.
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Energy
Generators
/ DER
Energy
Consum er
Energy
Aggregator
DSO
Retailer
W holesale
Market
energy &
pricing
distribute
energy &
flexibility$energy$
Trade energy/flexibility
for balancing
Energy
Prosum er
Energy
Consum er
… "eye ball" consumer
(own demand)
CAM … (central) grid role
Charging
Stat ion Op.
… use case
specific role
reliability 1
2
2
Metering information
3 comply to
agreements
3
4 demand & supply
forecasts
physical attacks
faulty devices
human errors...
energy
$
energy
trade
$
Regulator
$
Regulator … public authorities
$
long-term
price sensitivity of
demand
(assisting stability)
CAM
1
TSO
$energy
long-term trading/reservat.
metering
5 supply sbj. to
long-term pricing
agreements
5
Legend
Figure 57: “Classical” Electrical Grid Value Network
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9.1.1 Entities
9.1.1.1 “Eye ball” consumer in two flavours:
Energy consumer: The energy consumer is the classical consumer not providing any energy or
energy service to any other party.
Energy prosumer: The prosumer extends the role of a consumer by also generating energy
(see dedicated roles).
9.1.1.2 Energy sector:
Generation/Aggregation:
Energy Generators / Distributed Energy Resources (DER): Power plants and small energy
generators (e.g. PVs) producing the energy to be delivered to customers or traded on
markets.
Energy Aggregator: Aggregating individual DERs in order to act on (wholesale) markets
o Representing small actors (like individuals with their PVs) on wholesale market by
trading their resources appropriately
Market & Sales:
Wholesale Market: A (wholesale) market where it is possible to buy and sell energy and
demand flexibility, i.e., short-term (next day, intraday), long-term, and energy balancing
trading.
o Often operated by “Power Exchange” entity
o Scheduled energy exchange & flexibilities (e.g. in terms of primary, secondary, and
tertiary reserves)
o High transmission capacity required in order to avoid arbitrage business due to
different price levels in Control Areas accessing the market
o Incentives for precise reservation requests, e.g. tailored auction mechanisms
o Base load and peak load differentiation
o Trading of intermittent energy resources, e.g., realized in Spanish and US markets4
Retailer (Supplier, Trader): The retailer is the energy role having access to eyeball customers
by selling energy to them. It relies on an existing distribution network and the energy trading
on the wholesale market. It is responsible for acquiring required resources on the wholesale
market and may be confronted with compensation payments in case of unsatisfactory
physical delivery.
o Demand matching dynamicity in minutes (e.g. each 5 minutes) and price dynamicity
at ~ 30 minutes to 60 minutes5 at the minimum.
Distribution / Transmission / Balancing:
Distribution System Operator (DSO): According to the Article 2.6 of the Directive: "a natural
or legal person responsible for operating, ensuring the maintenance of and, if necessary,
developing the distribution system in a given area and, where applicable, its interconnections
4 http://www.smartpowergeneration.com/spg/discussion/flexibility_is_needed_-_but_th
5 National Electricity Market (Australia): http://eex.gov.au/energy-management/energy-procurement/energy-pricing/how-the-energy-market-operates/
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with other systems and for ensuring the long-term ability of the system to meet reasonable
demands for the distribution of electricity".
Control Area Manager (CAM): The European interconnected grid is subdivided into large number of
control areas that control the power that flows across it. These areas are largely independently
operated. Power meters are installed on every power line that crosses a control area boundary, and
the readings are transmitted online to the respective control centres. The Control Area Manger (CAM)
is then responsible for the system stability. The CAM calculates in advance how much
electricity will be needed to cross the control area boundaries to fulfil the supply contracts in
place. The power stations within the control areas are operated in accordance with these
schedules. In many countries a differentiation between the roles of TSOs (see next
paragraph) and CAMs may not exist.
o Corrects short-term and long-term imbalances of energy demand and supply caused by
retailers (whether due to incorrect energy reservation or unexpected demand/supply
patterns), e.g. by using cold reserves, and forwards incurred costs to retailers → balancing of
Control Area
o Actively trades on wholesale market
Transmission System Operator (TSO): According to the Article 2.4 of the Electricity Directive
2009/72/EC (Directive): "a natural or legal person responsible for operating, ensuring the
maintenance of and, if necessary, developing the transmission system in a given area and,
where applicable, its interconnections with other systems, and for ensuring the long- and
short-term (minutes) ability of the system to meet reasonable demands for the transmission
of electricity".
In addition, some use case specific roles may have to be acknowledged, which are detailed in Section
9.1.2.
9.1.2 Main Value Flows
The value flows capture relationships among actors. Here we identify three most significant value
flows and the main issue each of them addresses: (1) stability of the grid, (2) energy generation,
trading and delivery, and (3) regulation.
Stability of the grid: The CAM cares about stability on medium and long term and short term by
acting on the wholesale markets based on monitoring data and information exchanged with DSOs in
order to constantly balance the grid. The DSO and TSO globally coordinate agreements ensuring the
stability of the grid on coarser granular level, i.e. typically the interface is the CAM role.
Energy generation, trading & delivery: Generated resources are directly marketed on (wholesale)
marketplaces or first aggregated and then traded. Retailers then buy required energy to satisfy the
demands of their eyeball consumers. In some cases, energy may directly be sold by the aggregators
to industrial end consumers.
Regulation: The energy market is closely followed by regulatory authorities. The VN captures the
most important relationships where regulators (directly or indirectly) influence the business activities
of roles.
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9.2 SmartC2Net Value Network
With the transition towards smart grids, the resulting Value Network (cf. Figure 58) has to reflect a
series of changes.
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Energy
Generators
/ DER
Energy
Consum er
Energy
Aggregator
EV
Charging
Stat ion
Operator
I nfSP
DSO
Retailer
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Market
Vendors
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W eather /
Dem and) $
$ +
mete
ring in
fo.
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reserve
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., loo
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erv
ice
$ /
adve
rtis
em
ent
metering
infr. etc.
energy &
flexibility$energy
$
(dynamic) self-control
incentives ($)
& metering inf.
Energy
Prosum er
Energy
Consum er
… "eye ball" consumer
(own demand)
CAM … (central) grid role
Charging
Stat ion Op.
… use case
specific role
reliability 1
2
1
2
Metering &
compensation claims
3 compensation if not
agreement compliant
Com .
Netw ork
Ow ner
Com .
Service
Provider
network infr. $
4 demand & supply
forecasts
4
license $
5 Paid network services,
QoS guarantees, ...
5
attacks
faulty devices
human errors
communicationproblems
...
energy
$
energy
trade
modifieddemand
$
Regulator
$
$
registration$
$
TSO
Regulator
Com .
Netw ork
… communication
services
… public authorities
${ dynamic
trade-off
consumption –
trading
energy &
(dyn.) pricing
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modified
supply
Control
Area
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6 Trade energy/flexibility
for balancing the CA
6
metering
$
$
energy
long-term trading/reservat.
{all-smart-grid-actors}
Aggregated
EV Charging
I nfra-
st ructure
Managem ent
trade energy
7
7 Collective
energy trading
Legend
Figure 58 – SmartC2Net Value Network (with special consideration of chosen use cases)
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Main aspects of these changes are summarized as follows:
The dynamicity of interaction, information exchange and trading is most significantly
changed. More fine-granular interaction and cooperation is required – being enabled via
improved communication capabilities, i.e., introduction of communication service provider
to the VN
Capabilities for influencing demand and supply are substantially improved
Finer-granular metering capabilities in cooperation with modern communication
technologies are newly introduced
Balancing requirements in the distribution grid are substantially changed
The role of DSOs becomes more demanding when facing more DERs to be accommodated for
while maintaining a stable grid with the required power quality. Combined with liberalized
market structures, more intensive interaction between DSOs and retailers may be required;
however the current regulation of DSO role does not provide for it
In the LV grid, aggregation of all information from grid assets for technical and commercial
purposes. Data exchange between different actors on the LV grids and upstream.
More systematic integration of Electrical Vehicle (EV) charging, PVs, wind turbines, and
different size DERs or important new energy usages on the LV, MV and HV is required to
meet soaring demands and mitigate arising grid issues
Usage, collection and transmission of more information lead to more regulatory
requirements in respect of data management
Attack scenarios may also shift from physical-only scenarios to new constellations involving
communication networks and data manipulations.
On the other hand, the long-term business perspective modelled by the interaction of CAMs, DSOs,
and TSOs (see description below) will remain similar to the classical grid case.
The remainder of this section is organized in the description of entities and main value flows
depicted in the SmartC2Net Value Network representation.
9.2.1 Entities (Revised)
There are two different types of consumers: on the one-hand eyeball consumers aiming at satisfying
their own demands and on the other hand use case-specific additions.
9.2.1.1 “Eye ball” consumer
o Energy consumer: same as in the classical grid.
The energy consumer may (but need not) provide Smart Metering Data to all
interested parties and might allow flexible load scheduling (this a specific
function for use cases such as AMR / CEMS) as a 3rd party service for energy
efficiency.
o Energy prosumer: same as classical grid.
Adaptation of demand to the local supply may be offered as a 3rd party
service with high automation requirements
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E.g. via virtual metering, prosumers may directly trade their
resources with other consumers/prosumers. Virtual metering may
also be used in the case of separation of supply and demand location
of individual prosumers.
Dynamic demand & supply adaption as a service requires
customers/prosumers willingness to adapt their behaviour based on
perceived economic benefits.
9.2.1.2 Energy sector
Energy Generators / Distributed Energy Resources (DER): see classical grid.
o More flexibility and interaction with DSO may be required for balancing the grid
Energy Aggregator: see classical grid.
The energy supply is then utilised by market entities (trading & sales):
Wholesale Market / Local Markets: A (wholesale) market where it is possible to buy and sell
energy and demand flexibility
o See classical grid above
o Trading of local energy flexibilities / local balancing & shorter-term trading are
essential new features
More dynamicity required esp. for distribution grid resources trading, e.g. in
seconds, and supply-demand balancing, e.g. in milliseconds.
Higher importance of efficient trading of ancillary services (flexibilities), i.e.
entity requiring flexibility the most should be rewarded with an efficient
assignment (requires incentives and suitable auction mechanisms)
Retailer
o See classical grid above
o More efficient trading may be required with ability to snatch more efficient deals on
better metering/ forecasting
The following central grid roles are recognized:
Distribution System Operator (DSO): In addition to the classical case, the DSO is now
responsible for two-directional power flows and regional grid access for DERs, grid stability,
efficient integration/regulation of renewables at the distribution level and regional load
balancing (please also see CAM) for the case of smart grids. The DSO has central
responsibility for maintaining the stability and power quality in the distribution grid. Under
changed regulatory constraints, DSOs may aim at directly controlling local demand and
supply, offered as a special service. Beyond that, the use of metering information now
shared with the CAM (see next paragraph) may be diversified. The costs for maintaining the
power quality may also be diversified based on the new role of local supply or trading
(supply incentives; retailers compensation etc.) facilitating DSOs in active control of power
lines and flows in the distribution grid.
o Pricing updates (incentives) e.g. in milliseconds for balancing parts of the distribution
network
Control Area Manager (CAM):
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o See classical grid above
o Smart Grid: Clearer incentives / compensation mechanisms for unbalanced energy
demand & supply by retailers are required
Transmission System Operator (TSO): see classical grid.
9.2.1.3 Telco sector (complementary roles)
Communication Service Provider (CSP): The smart grid is about embedding advanced
communications and remote sensing into the electric power system to improve reliability,
optimize energy delivery, engage the consumer and expand the usage of renewable energy
resources. Wireless embedded machine-to-machine (M2M) solutions for utility automation
are becoming more important as they relate to the smart grid. Leveraging on established
relations with end user for wireless connectivity and on cost efficiency for deploying and
offering connectivity to DSO and TSO, Telecommunications companies will be playing an
increasingly greater role in common applications such as Automatic Meter Infrastructure,
Distribution Automation, Demand Response, supervisory control, data acquisition for SCADA,
building management, home energy management and electrical vehicle charging [FIER11].
The CSP is therefore the operator of the required communication network, i.e., provider of
telecommunication services like wireless access to meters. The CSP is also responsible for
providing Internet access to end customers at Customer Premises (CPs) – this may be
handled as bundled service or as independent contracts.
In addition the CSP can supply connectivity services to the DSO and the TSO for monitoring
and managing smart grid equipment. Depending on business conditions the connectivity
services provided could extend to a deeper integration between the CSP network and its
enablers and the DSO/TSO communication network and grid. In this case CSP can also enable
a series of market driver positively affecting the smart grid business case.
Communication Network Owner (CNO): CNOs are the owners of the communication
network on which the CSP operates. Often one entity may overtake both roles.
Vendor: Vendors provide infrastructure for communication networks, but also for metering
the grid and/or its data processing. Communication network vendors may act in the role of
the CSP by operating a network for a communication network owner (or several owners) due
to efficiency reason. This is a standard model common to mobile networks today.
3rd Party Forecasting Service: Beyond technical components assisting the forecasting of
supply or demand patterns in the future, external consulting services may be used.
9.2.1.4 Use case-specific roles
o EV Charging Station Operator (CSO): Operator of a Charging station – which is an
electrified parking lot with several Charging Stations (CSs) – is independent or owned
by Energy provider, DSO, etc. Thus, providing an equivalent service to filling stations
– please refer to the use case description for more detailed definitions.
Somehow cooperates with DSOs (ensuring sufficient energy can be delivered
to cars of customers)
Reservation system or comparable mechanism for balancing demand
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Establishment of a sustainable business case, e.g., by combination with other
services like paid parking lots or garages
o E-Mobility Service Operator: System including services for EV owners to find charging
stations as well as for the charging station operator to manage several charging
stations (may sometimes legally be owned be CSOs or CS chains).
Balancing of customers according ‘available energy’ (grid utilization, charging
slots, …)
Guidance of customers / providing lookup services, e.g. integration with
SatNavs or apps and the related integration with navigation service
providers.
Potential issue: Who operates this service across different charging station
providers? (Problem of universal access of information)
Link to Information Service Providers potentially visualizing or using provided
data
o Information Service Providers: Commonly available services provided by a third
party, e.g. weather information needed to predict PV production or Aggregated EV
Charging Infrastructure Management (see below):
May require access to data → potential problems with confidentiality of
information or varying market interests (e.g. competitors may not agree on a
single platform)
Openness of market access may be nutritious, but difficult
E.g., Aggregated EV Charging Infrastructure Management: Collectively acts on
energy markets, especially intra-day markets, for individual CSOs by
aggregating their energy demand requirements and placing bids at
marketplaces. If no such role exists, retailers may provide the energy directly
to CSOs–see Energy Consumer.
9.2.2 Main Value Flows (Revised)
The following paragraphs summarize and aggregate the main value flows in the VN. Further details
can be inferred from the visual representation as well as from the entity descriptions:
Stability of the grid: The CAM cares about short-, medium-, and long-term stability by carefully
monitoring the grid and influencing other actors to modify the demand or supply levels. Thus, CAMs
get active on the wholesale market, exchange information with DSOs and set energy reservation
requirements for retailers. CAMs finally correct imbalances between supply and demand through
reserves from the wholesale market. DSOs in contrast are responsible for assuring grid stability and
power quality on dynamic short-term basis in the distribution grid. Thus, in smart grids they may
actively influence demand of end customers or supply on the axis of DERs. This may be based on
incentives or regulated. The DSO and TSO globally coordinate agreements ensuring the stability of
the grid on coarser granular level, i.e. typically the interface is the CAM role. Long-term wholesale
agreements may also be dedicated to the role of TSO (besides the active balancing of the CAM role).
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Energy generation, provisioning & trading: In the case of SmartC2Net, DERs will have higher
importance and thus need to be better integrated and (decentrally) managed.
Regulation: Additional regulation may be necessary regarding the DER connection rules, the safety
and security of the smart grid and the protection of individuals, e.g., privacy and sensitive handling of
information.
Communication in Smart Grids: Communication networks are required for all smart grid entities due
to their requirement for exchanging information. All entities not operating their own network are,
hence, customers of a CSP. The most direct relationship may be established with DSOs probably
managing a series of sites with devices requiring the access to reliable communication infrastructure.
Nevertheless, also charging station owners, consumers, etc. may deliver information required for
balancing the smart grid or may receive information as added value (e.g. consumption statistics and
price signals). An important relationship also exists to consumers who themselves require Internet
access, but also Customer Premises Equipment (CPE) for realizing SmartC2Net use cases may require
connectivity. Thus, communication services essentially link the smart grid entities.
EV Charging: The central place for charging is the CS where demand and supply also need to be
balanced or coordinated. The purchasing of energy for each CS is typically collectively handled. This is
further assisted by a macroscopic view such as provided by E-Mobility Service Operators potentially
redirecting costumers in early stages. Such services may require a listing fee (registration) to be part
of a nation wide / EU-wide / global assistance. Eye-ball consumers may also pay fees for better
support or may have to consume advertisements (may not be possible on typical SatNav devices)
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10 Annex B - UC templates
10.1 USE CASE NAME: Medium Voltage Control
10.1.1 Description of the Use Case
10.1.1.1 Name of Use Case
Use Case Identification
ID Domain(s)
Name of Use Case
Distribution Grid
Management / Smart
Substation Automation/
Distributed Energy
Resources
Voltage Control in Medium Voltage Grids connecting DERs
10.1.1.2 Version Management
Version Management
Changes / Version Date Name
Author(s) or Committee
Domain
Expert
Area of
Expertise /
Domain /
Role
Title Approval
Status draft, for
comments, for
voting, final
v.0
based on the
CEN/CENELEC/ETSI
SGCG Use Case
WGSP-0200
25/01/2013 Giovanna Dondossola RSE
Roberta Terruggia RSE
ICT for
Distribution
Grid
Operation
and
Substation
Automation
Researchers Draft
v.1 11/03/2013 Giovanna Dondossola RSE
Roberta Terruggia RSE
Draft
v.2
EAB feedback,
protocols
15/05/2013 Giovanna Dondossola RSE
Roberta Terruggia RSE
Final
10.1.1.3 Scope and Objectives of Use Case
Scope and Objectives of Use Case
Related business case
Scope The introduction of Distributed Energy Resources (DERs) can influence the status of the
power grid. The behaviour of DERs can affects the capacity of the DSO to comply with the
contracted terms with the TSO and directly the quality of service of their neighbour grids.
DSO has to face with units whose behaviour is both unknown and uncontrollable and
investments on conventional reactive power control devices in substations may become
ineffective. This difficulty to meet the contracted terms and the quality of service standards
not only could be transferred into charges to the DSO, but also affects the TSO operation
because the scheduled voltages at grid nodes could not be observed and voltage stability
problems cannot be managed properly. In order to maintain stable voltages in the
distribution grid the Voltage Control function is introduced. This main goal can be extended
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in order to achieve other important objectives as supply ancillary services, minimize the cost
and the KWh consumption, provide reactive power support for distribution buses, reduce
energy losses and provide compatible combinations of the above objectives.
Objective The primary aim of this use case is to address the communication needs of a Voltage Control
(VC) function for medium voltage grids connecting Distributed Energy Resources (DERs). The
actions derived from the VC function are evaluated with the objective of defining an ICT
architecture suitable for security analysis. The VC use case is a didactic case illustrating the
need of cyber security in smart grid applications, first because its behaviour influences both
system operation and economy, second because of the high level inter-networking
requirements of its ICT architecture.
10.1.1.4 Narrative of Use Case
Narrative of Use Case
Short description – max 3 sentences
The Medium Voltage Control function optimizes the voltage profile and power flows to maintain a stable voltage at
customer site in a defined area of the distribution grid with distributed generators, flexible loads and other deployed power
equipment. The function involves different data flows both from internal and external actors that must be considered in
order to perform a cyber security analysis. The loss or corruption of the measurements and set points may cause cascading
effects with high impact on the power grid.
Complete description
The connection of DERs to medium voltage grids can influence the status of the whole power grid. Voltage profiles and
power flows in active distribution grids change dynamically, mainly because of the stochastic production of the renewable
sources. The power injected by distributed generators can overload feeder segments or raise the voltage beyond the limits
in parts of the grid. The behaviour of DERs can affect both the capacity of the DSO (Distribution System Operator) to comply
with the terms contracted with the TSO (Transmission System Operator) and the quality of service of their neighbour grids.
The automatic voltage regulation provided by the OLTCs (On Load Tap Changer) of the substation transformers and
compensation measures, as used in passive grids, may be insufficient to grant the supply requirements established by the
norm EN 50160. This difficulty to meet the contracted terms and the quality of service standards beside causing the
imposition of sanctions to the DSO, can also affect the TSO’s operation because grid nodes cannot maintain the scheduled
voltages and voltage stability problems cannot be managed properly.
The main purpose of the VC function is to monitor the status of the active distribution grid from field measurements and to
compute optimized set points for DERs, flexible loads and power equipment deployed in HV/MV substations. The function
monitors the voltage and power flow in critical points of the controlled grid. The status of the grid based on actual
measurements and grid topology as required by the control algorithm, is computed by a State Estimator, that creates an
accurate profile from available measurements. Optimization of the voltage profile is acquired by controlling reactive and
active power injection by distributed generators and energy storage equipment, and setting OLTCs and switched capacitor
banks. Besides, costs of control actions and load/generation forecasts in the area have to be taken into account to select
the appropriate control strategy. Considering the hierarchical architecture of the electric grid, a controlled area is a Medium
Voltage (MV) section of the grid, typically underlying a primary (HV/MV) substation and having points of common coupling
with low voltage distribution buses or the upper level grid.
The VC function is performed by the Controller on a node of a HV/MV substation control network. Figure 59 schematizes
the Voltage Control Function: starting from the inputs the function computes a Voltage profile and makes it operative by
sending set points to customer and utility devices.
In order to pursue the previously defined objective, the Controller computes the optimal states of the controllable devices
across the substation area. In a generic case, the optimization algorithm takes into account combinations of
technical/economic objectives and constraints, including requirements on power exchange at points of common coupling
with the upper grid. As part of a coordinated optimization process within the substation, suitable devices for control actions
are selected. Depending on the grid area to which the voltage control is applied and on the objectives of the optimization
process, generation/load units can be controlled directly by the Controller or via the Flexibility Operator (in the following
referred with the term Aggregator).
After every change of equipment state, due to an explicit request or to an automatic action, the substation is notified the
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new state or the operating point, inclusive of the information on available regulation ranges. If during the execution of the
optimization steps the topology of the grid changes, the application is interrupted and the solution is re-optimized. If during
the execution some operations are unsuccessful, then the solution is re-optimized excluding the malfunctioning devices. If
some controllable devices are unavailable for remote control, then the solution does not involve these devices but takes
into account their reaction to changes in operating conditions.
The main actors and how they interact are presented in
Figure 60. The control strategy requires information from sources external to the DSO domain. From the operational point
of view, the optimization function has to accept voltage regulation requests by the TSO whenever a transmission grid
contingency requires the application of preventive measures to avoid voltage collapse. Load and generation forecasts are
used to optimize the operation of distributed devices, while the economic optimization is based on market prices and DER
operation costs. A first major design assumption underlying the use case’s ICT architecture is that all the information
related to DER features, grid topology changes, requests by TSO, load/generation forecasts and market data are sent to the
Controller by the DMS (Distribution Management System) application in the DSO centre. This design choice preserves the
integrity of the distribution grid operation by limiting the number of communication channels at the substation level and
concentrating the communications with the external actors at the DSO centre level. In absence of criticalities, the VC
function is executed periodically (e.g. every 15 minutes) for optimization purposes, but its execution can be triggered
asynchronously by critical events (e.g. under/over voltage event, TSO requests, grid topology changes). The total response
time from the start of the elaboration to the end of the set point actuation, depends on actuation time constants of OLTC
and DER power electronics plus the communication overhead.
Figure 61 shows the UML Use case diagram where the actors and the (sub-)use case are depicted considering a normal
behaviour. The actors interact with the (sub-) use case “Voltage Control” that represents the main functionality of the
system.
Figure 63 shows how the actors and the functions of the Medium Voltage Control Use Case can be mapped to the smart
grid plane of Smart Grid Architecture Model (SGAM).
The main elements of the use case are placed into the Distribution and DER domains. The zones varying from the Market
zone of the Aggregator to the Field zone of control functions of the OLTC, Capacitor bank, DER and Flexible Load.
In the middle we have the Generation and Load Forecast functions placed in the cell Enterprise zone/Distribution domain
and integrated with the DMS.
TSO EMS and DMS Control Functions are in the Operation zone hosting all the active grid operation functions. The
Substation Automation System and the Voltage Control Functions with the SetPoint Calculation are placed in the Station
zone.
The architectural layout deployed for implementing the VC function depends on the responsibilities attributed to the use
case roles according to country-specific organisation and regulation. This Use Case assumes that the control of HV/MV
substations is under the responsibility of the DSO who has a network connection to the DERs. The data supply chain of the
VC function depends on several communication links enabling remote access from systems outside the perimeter of the
DSO operation. The DMS application in the DSO centre has permanent links (the green WAN in Figure 64) with four actors
(TSO, Aggregator, Generation Forecaster and Load Forecast); the Controller in the DSO substation has permanent
communication links (the red WAN in Figure 64) with third party DERs, possibly deploying heterogeneous communication
technologies, located in different geographical areas; communications between DMS and the substation automation and
control system through the DSO SCADA links (the blue WAN), eventually based on telecommunication services.
As seen the Medium Voltage Control use case involves different main area networks: Aggregator, TSO, DSO (Center), (DSO)
Substation, DER and Flexible Load networks. The communications can be intra area or inter area. In Figure 65 we observe a
schema of the different areas and of the communications. It is possible to identify the following different networks:
NW1: Wired LAN local to Substation, distinguishing different network segments that corresponds to separate
control layers, e.g. station, bay and process layers
NW2: Wireless/wired WAN that may use commercial cellular or private wireless technology. This network
connects the substation with the DER sites
NW3: Private wired WAN. This network connects the DSO Operation Center with the Substation. It may be based
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on dedicated communication services via wired WAN
NW4: Wired LAN local to DSO Operation Center, distinguishing different network segments that corresponds to
separate operation layers, e.g. DMS and MDMS
NW5: Wired WAN. This network connects the TSO Center with the DSO Operation Center. It may be based on
dedicated communication services via wired WAN
NW6: Public IP. This network connects the Aggregator with the DSO Enterprise Center
NW7: Wired WAN. This network connects the DSO Operation Center with the DSO Enterprise Center. Most
probably it will be based on dedicated communication services via wired WAN.
Note that the networks involving DER and Aggregator are WAN network and can be wired or wireless. In particular for the
network to the DER the wireless technology is desirable.
The main control and communication components are depicted in Figure 66. In this use case different communication
protocols are involved, in Figure 66 the main of them are represented.
The sequence diagram of the VC function is presented in Figure 69 where the information exchange is addressed.
One of the inputs of the VC function is the generation forecast: Figure 67 shows a sketch of the generation estimation
function. Figure 68 shows the sequence diagram with the main information flow.
By focusing on the core of the VC scheme, it is clear that the correct computation of the optimal set points depends on the
provision of correct operation and economic data from all communication sources. A malicious attack to one of the
communication links may cause either the loss of input data (generation forecasts, economic data from the Aggregator, TSO
requests, topological changes), or the loss of output setpoints, or the introduction of faked input/output values/setpoints.
The use case highlights sample communication attacks that may lead the control function to diverge from optimum set
point values or, even worse, to produce inadequate set points with cascading effects on connected generators. In Figure 62
an anomalous scenarios is represented through the (mis)use case diagram. The figure depicts how a (mis)user can attack
the system. Such abnormal scenarios to the VC function support the evaluation of the impact on the supplied power that
will depend on the size of the grid section, the amount of installed distributed generation, the control network topology
over the power grid structure and the extension of the attack itself. The evaluation of attack processes to the VC function is
aimed at identifying security controls to counteract those attacks which might compromise the voltage profile.
The global impact of such cyber attacks to the Voltage Control functions on the supplied power depends on the grid size
and the amount of distributed generation, both these factors varying on a geographical base. By focussing on the Italian
profile and targeting the integration of an amount of renewable energy of about 40 GW within 2020, the distribution grid
development plan requires the building of about 10% new HV/MV substations.
The analysis of the attack impact on the supplied power depends on the control network topology on the top of the power
grid structure. By applying an extreme case approach, the impact value associated to future smart grids endowed with the
Voltage Control function depends by the extension of the attack effect. For example, an attack to the DER network could
cause the disconnection of all the generators connected to the MV feeders of a given substation (e.g. less than 100MW); an
attack to the substation networks could be able to disconnect one or several substations (e.g. less than 1 GW); a control
centre attack, causing the disconnection of all the substations in a given control centre, could count 6 GW of unsupplied
power.
By mapping such impact values on the power scales identified by the SGIS working group, it results that the impact of those
cyber attacks to the communications of the Voltage Control functions may be associated, respectively, to the Medium, High
and Critical impact levels.
In section 4.2 of the template some anomalous scenarios are analysed with focus on the effect of different attacks (floding
based DoS and fake messages) to the communications involved in the Use Case. The related Sequence Diagrams are
presented in Figure 70, Figure 71, Figure 72, Figure 73 and Figure 74.
10.1.1.5 General Remarks
General Remarks
10.1.2 Diagrams of Use Case
Diagram of Use Case
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Third party DER Distributor’s device
Voltage Profile
Grid Topology
Fieldmeasurem
ent
Marketprices
ResourceOperation
costs
TSOsignals
LoadForecast
Voltage Control
Function
GenerationForecast
Figure 59 - Voltage Control
Aggregator TSOGeneration
Forecast
DMS
Medium Voltage Grid Controller (MVGC)
DER OLTCCapacitor
BankFlexible Load
Load Forecast
Figure 60 - Voltage Control - Actors Interactions
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Figure 61 - Voltage Control - Use Case Diagram
Figure 62 - Voltage Control - Use Case Diagram - attack scenarios
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Market
Enterprise
Operation
Station
Field
Process
Generation Transmission Distribution DERCustomerPremise
Aggregator
Load Forecast
Gen. Forecast
TSOEMS DMS
Sub.Autom. System
MVCG
OLTC CtrlCapacito Bank Ctrl
DER Ctrl
Flexible Load Ctrl
Figure 63 - Voltage Control – Mapping on SGAM
Aggregator
Secondary SubstationAutomation&Control
Primary Substation Automation&Control
Enterprise Comm. Network(WAN)
DER Flexible loads EnergyStorage
DSO
TSO
GenerationForecast
Transmission Grid
HV
MV
MV
LV
Control Control Control
Control
Control
Control
Control
Control
Technical Flexibility&Performance
Commercial Feasibility
& Flexibility
Load Forecast
Control
Control
OLTC
Control
Capacitor Bank
Control
DER Comm. Network(WAN)
DSO Comm. Network(WAN)
Figure 64 - Voltage Control - Overview of involved communications
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TSO Center
Aggregator Site
DER SiteDSO/Customer
DSO Operation Center
DSO Substation
FieldSubstation
AutomationSystem
DMS
Flexible load siteDSO/Customer
DSO Enterprise CenterEnterpriseSystems
NW6
NW5
NW7
NW3
NW2
NW4
NW1 MVGC
Figure 65 – Voltage Control – Communications
Figure 66 – Voltage Control - Component Layer
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Automated
Meter Management
Weather Forecast
Grid DB Management
Generation Forecast
DMS
Figure 67 - Generation Forecast
Figure 68 - Generation Forecast - Sequence Diagram
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Figure 69 – Voltage Control - Sequence Diagram
Figure 70 - Voltage Control - DoS Attack to DER
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Figure 71 - Voltage Control - DoS Attack to MVGC
Figure 72 - Voltage Control - Fake DER Set point
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Figure 73 - Voltage Control - Fake DER Set point (Man in the Middle)
Figure 74 - Voltage Control - Fake TSO signal
10.1.3 Technical Details
10.1.3.1 Actors: People, Systems, Applications, Databases, the Power System, and Other
Stakeholders
Actors
Grouping (Community) Group Description
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Actor Name see Actor List
Actor Type see Actor List
Actor Description see Actor List
Further information
specific to this Use Case
Meter Data Management
System
System System for validating, storing,
processing and analyzing large
quantities of meter data
Weather forecast System Provides weather forecast used for
different utility business processes
(scheduling, planning, operational
planning, operation ...)
Grid DB Management System System that manages the DB of the
electric network consistency
Aggregator Role Offers services to aggregate energy
production from different sources
(generators) and acts towards the grid
as one entity, including local
aggregation of demand (Demand
Response management) and supply
(generation management). In cases
where the aggregator is not a supplier,
it maintains a contract with the
supplier.
Transmission System
Operator (TSO)
Role According to the Article 2.4 of the
Electricity Directive 2009/72/EC
(Directive): "a natural or legal person
responsible for operating, ensuring the
maintenance of and, if necessary,
developing the transmission system in
a given area and, where applicable, its
interconnections with other systems,
and for ensuring the long-term ability
of the system to meet reasonable
demands for the transmission of
electricity". Moreover, the TSO is
responsible for connection of all grid
users at the transmission level and
connection of the DSOs within the TSO
control area.
Generation forecast System Computes forecast for renewable
generation in controlled area based on
weather forecast
Load forecast System Computes forecast for load in
controlled area
DMS System Distribution Management System a
system which provides applications to
monitor and control a distribution grid
from a centralized location, typically
the control center. A DMS typically has
interfaces to other systems, like an GIS
or an OMS
Medium Voltage Grid System Medium Voltage Grid Controller
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Controller (MVGC) implementing the Voltage Control
Function
Substation Automation
System (SAS)
System Substation Automation System
implementing the automation
sequences and the control functions of
interfacing process level control
devices
DER Device Generic Distributed Energy Resource -
"DER devices are generation and
energy storage systems that are
connected to a power distribution
system" (IEC 62357)
Flexible load Device Load that can be modulated
Capacitor bank Device A switchable bank of shunt capacitors. May be generalized as
Shunt Compensator
(A section of a shunt
compensator is an
individual capacitor or
reactor). (IEC 61970)
OLTC Device On Load Tap Changer. Mechanism for
changing transformer winding tap
positions.
10.1.3.2 Preconditions, Assumptions, Post condition, Events
Use Case Conditions
Actor/System/Information/Contract Triggering Event Pre-conditions Assumption
Medium Voltage Grid Controller
The Voltage Control algorithm
applies to a MV grid under a
Primary Substation and operate
only controllable device directly
installed on the MV grid.
DER ancillary services
The use of DER ancillary services
is defined by contracts or regional
regulation.
Substation Control System can
operate only DERs having
subscribed some agreement with
Distribution System Operator.
Generally only a subset of
installed DER is controllable.
Costs of DER ancillary services
The algorithm takes in account
dispatching costs for DER active
and reactive power.
Different remuneration of
ancillary services offered by DERs
are possible:
- administrated price: fixed price established by Authority bodies;
- Market scheme: DER operators
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fix prices for their services (not fully realistic for MV networks);
- Mixed approach.
DER storage
It is assumed that storage units
are owned and operated directly
by the Distribution Company in
order to increase grid control
capabilities.
There is an integral constraint on
control strategies to maintaining
the same level of charge on 24
hour time horizon.
DMS
DMS knows:
- DERs features (Nominal power, Capability, Controllability, etc.)
- Load forecast for each MV load,
- Generation forecast for each DER, controllable or not.
Grid measurements
Grid measurements are available
from substation devices and from
DERs.
State Estimation
State estimation of controlled MV
grid under a Primary Substation is
performed by either the Medium
Voltage Grid Controller or the
Control Centre (DMS).
Execution of control voltage
algorithm
Control loop is executed:
- Periodically (15’) - On critical
under/overvoltage event - On grid topology change
Signals related to grid stability
(normal, critical, alarm, …)
coming from TSO can influence
the execution of control voltage
algorithm (e.g. changing
optimization criteria or overriding
commands).
Generation Forecast
Forecasts updated every 12 hours
with granularity of 1 hour. Valid
for 36 hours
10.1.3.3 References /Issues
References
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No
.
References Type Reference Status Impact on Use Case Originator/O
rganisation
Link
1 European Report SGCG/M490/E_Smart
Grid Use Case
Management Process
— Use Case
Collection,
Management,
Repository, Analysis
and Harmonization
Public Specification CEN/CENELE
C/ETSI
2 Use Case SGSP Working Group
Use Case WGSP-0200
Public Specification CEN /
CENELEC /
ETSI
3 European Report SGCG/M490/B_Smart
Grid Report First set
of Standards Version
2.0 Nov 16th
2012
Public Standards CEN/CENELE
C/ETSI
4 International
Standard
IEC 60870-5-104 IS Communication IEC TC57
5 International
Standard
IEC 61850(-7-420) IS Communication /
Data Model
IEC TC57
6 International
Standard
IEC 62351 TS Security IEC TC57
7 International
Standard
NIST SP800-53 & 800-
82, IR 7628
SP, IR Security NIST
8 International
Standard
IEC 61970 IS Data Model IEC TC57
9 International
Standard
IEC 61968 IS Data Model IEC TC57
10 Article Monitoring and
Control of Active
Distribution Grid
Public Specification CIRED 2012 http://www.cired2
012-workshop.org/
11 Article Impact of DER
Integration on the
Cyber Security of
SCADA Systems –The
Medium Voltage
Regulation Case
Study
Public Security Issue CIRED 2012 http://www.cired2
012-workshop.org/
12 Project FINSENY Public Specification EU FP7
project
http://www.fi-ppp-
finseny.eu/
10.1.3.4 Further Information to the Use Case for Classification / Mapping
Classification Information
Relation to Other Use Cases Grid monitoring and control, State Estimation, Generation management, Load management, Storage management,
Advanced DMS and Distribution Automation, Grid emergency management, Power quality, Weather forecast, market signal
Management
Level of Depth
High Level
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Prioritisation
Needed for countries with high DER penetration on distribution grid
Generic, Regional or National Relation
Generic
View
Technical
Further Keywords for Classification
Voltage and VAR Control, DER Management, Cyber security, ICT architectures
10.1.4 Step by Step Analysis of Use Case
Scenario Conditions
No. Scenario
Name
Primary
Actor
Triggering
Event
Pre-Condition Post-Condition
4.1.1 Generation
Forecast
Estimation
Generation
forecast
Periodically New info available New generation forecast available
4.1.2 Information
acquisition
DMS Periodically /
Asynchronous
TSO signal or new
info
Info integrated with local data
4.1.3 Forwarded info DMS Periodically
/Asynchronous
DMS receives new
data
Medium Voltage Grid Controller obtains
input for the control algorithm
4.1.4 Grid
measurement
dispatch
Third party DER
/ Distributor’s
device
Periodically Field dispatches
new measurements
Medium Voltage Grid Controller obtains
new measurements
4.1.5 Forward of grid
measurements
Medium
Voltage Grid
Controller
Periodically Substation Control
System has new
SCADA and DER
measurements
DMS receives new measurements
4.1.6 Execution of
control voltage
algorithm
Medium
Voltage Grid
Controller
Values out of
range
The state is not
acceptable
Computation of new setpoints (horizon 24
h)
4.1.7 Set Setpoints Substation
Automation
System /
Medium
Voltage Grid
Controller
New setpoint New setpoints
computed
Devices change their settings
4.2.1 DoS Attack: DER DER Attacker launches
an attack
Missing measurements
4.2.2 DoS Attack:
Medium Voltage
Grid Controller
Medium
Voltage Grid
Controller
Attacker launches
an attack
Missing measurements
4.2.3 Fake DER Setpoint DER Attacker launches
an attack
Abnormal behaviour
4.2.4 Fake DER Setpoint
(Man in the
Middle)
DER Attacker launches
an attack
Abnormal behaviour
4.2.5 Fake TSO signal Medium
Voltage Grid
Controller
Attacker launches
an attack
Incorrect State estimation leads to
abnormal behaviour
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10.1.4.1 Steps – Normal
Scenario 4.1.1
Scenario
Name :
Generation Forecast Estimation
Step
No.
Event Name of
Process/Activit
y
Description of
Process/Activity
Servic
e
Information
Producer
(Actor)
Informatio
n Receiver
(Actor)
Informatio
n
Exchanged
Technical
Requirement
s R-ID
1 Periodic Meter data
collection
Collecting data from
meters about the
grid status
GET Meter Data
Management
System
Generation
Forecast
Grid status
2 Periodic
every 12
hours
Weather data
collection
Collecting data from
weather forecast
service about the
weather forecast
GET Weather
forecast
Generation
Forecast
Weather
forecast
3 Periodic Grid topology
data collection
Collecting data from
Grid DB
Management about
the grid topology
GET Grid DB
Management
Generation
Forecast
Updated
Grid
Topology
4 Periodic
every 12
hours
Forecast
estimation
Calculate the
forecast of active
power generation
EXECU
TE
Generation
Forecast
Generation
Forecast
Updated
Generation
forecast for
each DER
Scenario 4.1.2
Scenario
Name :
Information acquisition
Ste
p
No.
Event Name of
Process/
Activity
Description of
Process/Activity
Service Information
Producer
(Actor)
Information
Receiver
(Actor)
Information
Exchanged
Technical
Requirements
R-ID
1 TSO
changes
algorithm
paramete
rs
(Asynchr
onous)
TSO
message
Send signals influencing
the execution of
control voltage
algorithm (e.g.
changing optimization
criteria or overriding
commands).
REPORT/C
REATE
TSO DMS TSO Signals
2 Periodic
every 12
hours
DER
Generatio
n Forecast
Update Generation
forecast for each DER
CREATE Generation
forecast
DMS Updated
Generation
forecast for
each DER
3 Periodic Load
Forecast
Update load forecast CREATE Load
forecast
DMS Updated
Load
forecast
4 Periodic Energy /
Ancillary
Costs
Update Energy /
Ancillary Costs
CREATE Aggregator DMS Updated
Energy /
Ancillary
Costs
5 Periodic Load/Gen
Customer
program
Programs of load and
generation of the
customers
CREATE Aggregator DMS Load/Gen
Customer
program
Scenario 4.1.3
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Scenario Name : Forwarded info
Step
No.
Event Name of
Process
/Activity
Description of
Process/Activity
Service Informatio
n
Producer
(Actor)
Information
Receiver
(Actor)
Informatio
n
Exchange
d
Technical
Requirements R-
ID
1 TSO
signal
received
TSO
changes
algorithm
paramete
rs
(Asynchr
onous)
TSO
signal
forward
Send signals influencing
the execution of control
voltage algorithm (e.g.
changing optimization
criteria or overriding
commands).
CREATE DMS Medium
Voltage Grid
Controller
TSO Signals
2 Periodic Update
DER
features
informati
on
Update Features
information (Nominal
power, Capability,
Controllability, etc.) of
DER installed on the MV
grid
REPORT DMS Medium
Voltage Grid
Controller
Updated
Load/DER
Features
3 Grid
topology
changes
Update
grid
change
Send configuration
change of the controlled
MV grid (grid topology
reconfiguration, new
DER/load installation)
REPORT DMS Medium
Voltage Grid
Controller
Updated
Grid
Topology
4 Periodic
every 12
hours
Forward
generatio
n
forecast
Update Gen forecast for
each DER
CREATE DMS Medium
Voltage Grid
Controller
Updated
Gen
Forecast
for each
DER
5 Periodic Forward
load
forecast
Update Load / forecast
for each Load
CREATE DMS Medium
Voltage Grid
Controller
Updated
Load
Forecast
for each
Load
6 Periodic Forward Energy /
Ancillary
Costs
Update Energy /
Ancillary Costs
CREATE DMS Medium
Voltage Grid
Controller
Updated
Energy /
Ancillary
Costs
Scenario 4.1.4
Scenario
Name :
Grid measurement Acquisition
Ste
p
No.
Event Name of
Process
/Activity
Description of
Process/Activity
Service Informatio
n
Producer
Information
Receiver
(Actor)
Informatio
n
Exchange
Technical
Requirements
R-ID
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(Actor) d
1 Periodic
seconds
OLTC
Measure
ments
OLTC Measurements CREATE OLTC
Substation
Automation
System
OLTC
Measurem
ents (P,Q,V)
2 Periodic
seconds
Capacitor
bank
Measure
ments
Capacitor bank
Measurements
CREATE Capacitor
bank
Substation
Automation
System
Capacitor
bank
Measurem
ents
(P,Q,V)
3 Periodic
seconds
DER
Measure
ments
DER Measurements CREATE DER Medium
Voltage Grid
Controller
DER
Measurem
ents
(P,Q,V)
4 Periodic
seconds
Flexible
load
Measure
ments
Flexible load
Measurements
CREATE Flexible
load
Medium
Voltage Grid
Controller
Flexible
load
Measurem
ents
(P,Q,V)
5 Periodic
seconds
Field
Measure
ments
OLT/Capacitor bank
Measurements
CREATE Substation
Automatio
n System
Medium
Voltage Grid
Controller
OLTC/Capa
citor bank
Measurem
ents
(P,Q,V)
Scenario 4.1.5
Scenario
Name :
Forward of grid measurements
Step
No.
Event Name of
Process
/Activity
Description of
Process/Activity
Service Informatio
n
Producer
(Actor)
Information
Receiver
(Actor)
Informatio
n
Exchange
d
Technical
Requirements
R-ID
1 Periodic Measure
ments
forward
Medium Voltage Grid
Controller forward the
SCADA and DER
measurements
CREATE Medium
Voltage
Grid
Controller
DMS SCADA and
DER
measureme
nts
Scenario 4.1.6
Scenario
Name :
Execution of control voltage algorithm
Step
No.
Event Name of
Process/Activity
Description of
Process/Activity
Service Information
Producer
(Actor)
Information
Receiver
(Actor)
Information
Exchanged
Technical
Requirements
R-ID
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10.1.4.2 Steps – Alternative, Error Management, and/or Maintenance/Backup Scenario
Scenario 4.2.1
Scenario Name: DoS Attack: DER
Step
No.
Event Name of
Process/Activity
Description of
Process/Activity
Service Information
Producer
Information
Receiver
Information
Exchanged
Technical
Requirements
R-ID
1 Attacker
launches
DoS Attack The attack floods
the DER with
CREATE Attacker DER Anomalous
traffic
1 Periodic
every 15
/Triggered
by grid
topology
changes
minutes /
State Estimation Execute State
Estimation
EXECUTE Medium
Voltage Grid
Controller
Medium
Voltage Grid
Controller
Estimation
of the Grid
state
2 State from
state
estimation
Check state Check if the
parameters are within the limits
EXECUTE Medium
Voltage Grid
Controller
Medium
Voltage Grid
Controller
Estimation
of the Grid
state
3 Triggered
by TSO
signal /
Set point
calculation
Optimized Set
point calculation
Algorithm
(horizon 24 hours)
EXECUTE Medium
Voltage Grid
Controller
Medium
Voltage Grid
Controller
Set point
Calculation
Scenario 4.1.7
Scenario
Name :
Set Setpoints
Step
No.
Event Name of
Process/Activity
Description of
Process/Activity
Service Information
Producer
(Actor)
Information
Receiver
(Actor)
Information
Exchanged
Technical
Requirements
R-ID
1 New set
point
OLTC / Capacitor
bank Set point
Send OLTC/
Capacitor bank
Set point
CREATE Medium
Voltage Grid
Controller
Substation
Automation
System
Capacitor
bank Set
point ΔQ +/-
ΔV +/-
OLTC Set
point
ΔV +/-
2 New set
point
OLTC / Capacitor
bank Set point
Send OLTC /
Capacitor bank
Set point
CREATE Substation
Automation
System
OLTC /
Capacitor
bank
Capacitor
bank Set
point ΔQ +/-
ΔV +/-
OLTC Set
point
ΔV +/-
3 New set
point
DER Set point Send DER Set
point
CREATE Medium
Voltage Grid
Controller
DER
DER Set
point
ΔP +/-
ΔQ +/-
4 New set
point
Flexible load Set
point
Send flexible load
Set point
CREATE Medium
Voltage Grid
Controller
Flexible load
Flexible load
Set point
ΔP +/-
ΔQ +/-
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an attack abnormal
messages
2 DER is
under
attack
DER
communications
down
The Medium
Voltage Grid
Controller doesn’t
receive the
measurements
from DER
GET DER Medium
Voltage Grid
Controller
Missing
measurements
Scenario 4.2.2
Scenario Name : DoS Attack: Medium Voltage Grid Controller
Step
No.
Event Name of
Process/Activity
Description of
Process/Activity
Service Information
Producer
Information
Receiver
Information
Exchanged
Technical
Requirements
R-ID
1 Attacker
launches an
attack
DoS Attack The attack floods
the MVGC with
abnormal
messages
CREATE Attacker Medium
Voltage Grid
Controller
Anomalous
traffic
2 Medium
Voltage Grid
Controller is
under attack
Medium Voltage
Grid Controller
communications
down
The DER and
SCADA
measurements
don’t reach the
DMS
GET Medium
Voltage Grid
Controller
DMS Missing
measurements
Scenario 4.2.3
Scenario Name : Fake DER Setpoint
Step
No.
Event Name of
Process/Activity
Description of
Process/Activity
Service Information
Producer
Information
Receiver
Information
Exchanged
Technic
al
Require
ments
R-ID
1 Attacker
launches
an attack
Fake setpoint The attacker
sends a fake
setpoint to DER
CREATE Attacker DER DER Setpoint
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2 DER
changes
its
settings
Abnormal
execution
DER receives a
setpoint and
changes its
settings
EXECUTE DER DER Settings
Scenario 4.2.4
Scenario
Name :
Fake DER Setpoint (Man in the Middle)
Step
No.
Event Name of
Process/Activity
Description of
Process/Activity
Service Information
Producer
Information
Receiver
Information
Exchanged
Technical
Requirements
R-ID
1 Medium
Voltage
Grid
Controller
sends
DER
setpoint
Message
interception
Attacker
intercepts the
setpoint message
from Medium
Voltage Grid
Controller
CREATE Medium
Voltage Grid
Controller
Attacker DER setpoint
2 Attacker
changes
message
Message change Attacker changes
the values of
setpoint
EXECUTE Attacker Attacker Fake DER
setpoint
3 Attacker
forwards
the fake
message
Message forward Attacker forwards
the fake message
CHANGE Attacker DER Fake DER
setpoint
4 DER
changes
its
settings
Abnormal
execution
DER receives a
setpoint and
changes its
settings
EXECUTE DER DER Settings
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Scenario 4.2.5
Scenario Name : Fake TSO signal
Step
No.
Event Name of
Process/Activity
Description of
Process/Activity
Service Information
Producer
Information
Receiver
Information
Exchanged
Technical
Requirements
R-ID
1 Attacker
launches an
attack
Fake TSO signal Attacker sends a
fake TSO signal
message
CREATE Attacker Medium
Voltage Grid
Controller
TSO signal
2 Receive of
TSO signal
State Estimation MVGC executes
algorithm
EXECUTE Medium
Voltage Grid
Controller
Medium
Voltage Grid
Controller
Incorrect
state
estimation
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10.1.5 Information Exchanged
Information Exchanged
Name of Information
Exchanged
Description of Information Exchanged Requirements to information data R-ID
Updated Grid Topology Information regarding the characteristics of the
grid elements (nodes, loads, generators and
lines). Configuration change of the controlled
MV grid (grid topology reconfiguration, new
DER/load installation)
Standard Protocols: IEC 60870-5-104, TCP/IP
Weather forecast Weather forecast, weather data Standard Protocols: Web services, TCP/IP
TSO signals Signal influencing the execution of control
voltage algorithm (e.g. changing optimization
criteria or overriding commands).
Voltage setting, Reactive Power setting, AVR
inclusion/exclusion
Standard Protocols: IEC 60870-5-104, TCP/IP
Updated generation forecast Active power production plan on an hour base
on a time horizon of 36 hours (36 values of
active power). Generation coefficient 0<C<1
Standard Protocols: IEC 61968-100, IEC 60870-
6, IEC 60870-5-104, TCP/IP
Updated load forecast The future load is predicted on the basis of
reference loads (seasonal patterns), stochastic
fluctuations, active demand effects, weather
forecast, day type. Load coefficient 0<C<1
Standard Protocols: IEC 61968-100, IEC 60870-
6, IEC 60870-5-104, TCP/IP
Updated Energy/Ancillary costs Costs for the modulation of active and reactive
power and reward schemes
Standard Protocols: IEC 62325, IEC 61968-100,
IEC 60870-6, IEC 60870-5-104, TCP/IP
Updated Load/DER Features Update Features information (Nominal power,
Capability, Controllability, etc.) of DER
Standard Protocols: IEC 61968, IEC 61850-7-
420, IEC 60870-5-104, TCP/IP
OLTC Measurements and States Voltage values, AVR included/excluded Standard Protocols: IEC 61850-8-1, IEC 60870-
5-104, TCP/IP
Capacitor bank Measurements and
States
Voltage values, Reactive power values,
included/excluded
Standard Protocols: IEC 61850-8-1, IEC 60870-
5-104, TCP/IP
DER Measurements Voltage values, Active and Reactive power
values
Time Requirements: 4 sec [refresh time on the
CC HMI]
Standard Protocols: IEC 61850-7-420, IEC
61850-8-1, IEC 61850-90-5, IEC 61850-90-1, IEC
60870-5-104, TCP/IP, UDP/IP
Flexible load Measurements Voltage values, Active and Reactive power
values
Standard Protocols: IEC 61850-8-1, IEC 61850-
90-5, IEC 61850-90-1, IEC 60870-5-104, TCP/IP,
UDP/IP
Grid state estimation Estimation of the current state of the grid Standard Protocols: IEC 61970, IEC 61968, IEC
60870-5-104, TCP/IP
Capacitor bank Set point Capacitor bank Set point ΔQ +/-
ΔV +/-
Standard Protocols: IEC 60870-5-104, IEC
61850-8-1, TCP/IP
OLTC Set point OLTC Set point
ΔV +/-
Standard Protocols: IEC 60870-5-104, IEC
61850-8-1, TCP/IP
DER Set point DER Set point
ΔP +/-
ΔQ +/-
Standard Protocols: IEC 61850-7-420, IEC
60870-5-104, IEC 61850-90-5, IEC 61850-90-1,
IEC 61850-8-1, TCP/IP
Flexible load Set point Flexible load Set point
ΔP +/-
ΔQ +/-
Standard Protocols: IEC 60870-5-104, IEC
61850-90-5, IEC 61850-90-1, IEC 61850-8-1,
TCP/IP
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10.1.6 Common Terms and Definitions
Common Terms and Definitions
Term Definition
AVR Automatic Voltage Regulator
DER Distributed Energy Resource
DMS Distribution Management System
DSO Distribution System Operator
EMS Energy Management System
GIS Geographic information system
HV High Voltage
IP Internet Protocol
LAN Local Area Network
MV Medium Voltage
MVGC Medium Voltage Grid Controller
OMS Outage Management System
OLTC On Load Tap Changer
PEV Plug-in Electric Vehicle
P(f) Active power P(f) is a function of frequency f. The active power generated and active power consumed
at each moment should be equal. A deviation from this equilibrium results in a deviation from the 50 Hz
frequency. So keeping this equilibrium between active power generation and consumption means
maintain frequency
Q(U) Reactive power Q(U) is a function of voltage U. The reactive power on the grid should be kept in
equilibrium. Reactive power is an extra load for the grid, leaving less capacity for active power, resulting
in a local voltage drop. So keeping reactive power in equilibrium means maintaining voltage.
SAS Substation Automation System
SGAM Smart Grid Architecture Model
TSO Transmission System Operator
V Voltage
VPP Virtual Power Plant
WAN Wide Area Network
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10.2 USE CASE NAME: Electrical Vehicle Charging in Low Voltage Grids
10.2.1 Description of the Use Case
10.2.1.1 Name of Use Case
Use Case Identification
ID Domain(s)
Name of Use Case
Distribution Grid Electric Vehicle Charging in Low Voltage Grids
10.2.1.2 Version Management
Version Management
Changes /
Version
Date Name
Author(s) or Committee
Domain
Expert
Area of
Expertise /
Domain /
Role
Title Approval
Status draft, for comments,
for voting, final
0.2 Jan.2013 SB, JG/FTW draft
0.4 Feb/Mar
13
SB, JG/FTW draft
1.0 8.03.13 SB/JG FTW V1.0 released
1.1 27.03.13 SB Changes after
review
1.2 25.04.13 SB EAB feedback
1.3 31.05.13 SB/JG Add “Aggregated
charging
infrastructure
entity”, price info
10.2.1.3 Scope and Objectives of Use Case
Scope and Objectives od Use Case
Related business case
Scope Low voltage distribution grids
Markets
Distribution grid operation Objective Satisfy the charging demands of arriving EVs in such a way that the
generated and stored energy is efficiently used and the grid is not overloaded.
Enable electrical vehicle charging to become a flexible consumption resource that can be used to balance energy and power resources in the LV grid along with decentralized production as well as other loads (e.g. households).
Provide a system architecture enabling interoperation between new actors such as charging station operators (charging aggregator) and their connection to existing actors such as DSOs and energy providers.
Enable DSOs to monitor state of low voltage grid under EV load conditions.
10.2.1.4 Narrative of Use Case
Narrative of Use Case
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Short description – max 3 sentences
Charging of electrical vehicles in low voltage grids is challenging due to highly synchronized demand patterns of charging as
well as high loads. This use case covers the controlled charging of electrical vehicles in a low voltage grid, taking into
consideration the EV owner, a charging infrastructure owner/provider as well as the DSO. Regarding the latter, the use case
aims to utilize the high demand flexibility of the charging process to balance grid and energy in the low voltage grid.
Complete description
The overall electrical vehicle charging deployment overview is depicted in
Figure 75. It consists of 5 main parts listed in the following:
1) A Charging Station installation is provided that can be represented by a) private charging scenario with a few charging spots. The private sector at home includes garages, carports and parking grounds around single or multi-family homes. b) In the semi-public sector, the charging stations are operated for example in parking grounds or underground parking of hotels, banks, gastronomy companies, shopping centres or at car dealerships c) be represented by a public charging scenarios where several charging spots are controlled by a charging station controller. The charging spots are public, meaning that a public group of EV owners can charge their electrical vehicles at them.
2) Local LV Grid resources being local production and storage that will operate in an interplay with the electrical vehicle charging to provide energy management services towards the grid as well as cost and environmentally efficient charging operations.
3) Secondary Substation containing DSO equipment to manage metering, monitoring as well as grid control.
4) The DSO domain representing the link of the low voltage grid to the DSO operations; including requirements towards significant low voltage grid sub-systems such as electrical vehicle charging.
5) The “Cloud” representing services in the open networks/internet used to: a) provide a market for trading energy and flexibility resources, b) to enable information needed for local control (e.g. weather) and finally, c) for a charging station operator to coordinate the allocation on its CS controllers, define prices for its services and provide routing services for the EV owners/drivers (using the Charging Station Routing). For this service, the CSO would pay.
Details of the individual components/systems are described in the actor lists.
For the given electrical vehicle deployment scenario a total of 7 networks have been identified. A
network here represents a given network infrastructure with a specific purpose. In reality, each
network may be realized by different or similar technologies or several networks may be operated as
a single network. This identification of different networks enables to define different deployment
scenarios and resulting networking architectures in which advanced control tasks must operate. A
scenario and its analysis can help to clarify which networks are involved and thereby how the
communications may affect the scenario. The networks are defined as follows:
Network 1 – Metering. The metering network is owned by the DSO or a metering infrastructure
operator. It is a network used to collect smart meter data measurements at the last mile. The smart
meter network is usually based on powerline communications, cellular or proprietary wireless
solutions.
Network 2 – Sub-station network. This network is an internal bus-network in the secondary
substation. It is owned by the DSO and connects equipment in the substation. May be based on
Ethernet.
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Network 3 – Public IP Network. The Public IP network represents the open Internet. This is the
easiest platform for third parties to provide their services, such as routing services to EV users, or
weather services. The public IP network can be based on everything from wired xDSL based
technologies to cellular data access.
Network 4 – eCar Communication. This communication is between the charging station and the
electrical vehicle itself. The communication is usually wired and may be running through the charging
cable itself. Information about the state of the car, e.g. state of charge, preferred charging speed,
etc. may be provided through this network.
Network 5 – Private IP Network The private IP network represents a local network infrastructure
utilized by the infrastructure owner to connect local elements. For instance charging spots may be
connected to the charging station through this network. It could be based on PLC or Ethernet.
Network 6 - LV Grid Management Network. The DSO may choose to deploy an own closed
networking architecture used for grid components to communicate. Thus could be to communicate
with inverters, protection devices as well as sensors in the grid.
Network 7 – DSO Network. The DSO network is the network connecting the DSO management and
control systems (e.g. SCADA) towards the secondary sub-station. These networks are usually closed.
They may be based on fibre put out by the DSO as the cables to substations were put in the ground.
To define how these components are foreseen to interact over the provided networks, a total of
three main scenarios have been defined. 1) A charging scenario, 2) an energy and power
management scenario and 3) a market scenario. Each scenario is described pictorially through a use
case diagram identifying actors, their sub-use cases and their interactions to support the scenario
and a message sequence diagram to define how components and actors communicate. These
scenarios are briefly described in the following:
Charging Scenario:
See Figure 76 and Figure 77.
This scenario has the EV Owner/driver as the main actor. The scenario defines how the EV
Owner/driver is interested in charging his/her electrical vehicle and having it fully charged when
needed again. In the private charging case it is clear where to charge. In the public charging case, also
a pre-charging phase exist where EV owners/drivers can search for charging stations.
The charging operations are controlled locally by a charging station controller. The controller is
responsible for trying to make charging cheapest (for the EV owner if he/she pays after energy
consumption and/or the charging station (infrastructure) operator, if he/she provides a flat-rate
charging service. The control further needs to take into consideration local limitations provided by
the DSO such as grid limits or load objectives provided by the operator to maintain the service quality
and help improve utilization of local resources.
The pre-charging phase called reservation is not mandatory, but allows a better planning of the
resources at a public charging station and improves the probability to find available resources when
the EV user tries to plug in. The use case continues with plug-in in which the schedule is updated. A
periodic event calculates the grid situation taking into account generation, consumption and storage
and might lead to a plan update. The charging period ends with the stop charging event created
either by completion of the plan or by a plug-out and leave event.
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Energy and Power Management:
See Figure 78 and Figure 79.
This scenario considers the DSO as the main actor. Based on local LV grid conditions as well as
requirements on MV level, the DSO tries to balance the power resources in the low voltage grid. The
goal is to make sure the grid operation is within acceptable limits, to ensure that grid components
are not overloaded and also to make sure that enough energy can be provided to supply the charging
service. The DSO provides requirements towards local production, storage and consumption. E.g. the
DSO will ensure to signal to the charging station controller when grid power resources are sparse or
the voltage is too low as well as to request certain load flexibility behavior that enables to balance
the grid.
Energy Market Operation:
See Figure 80 and Figure 81.
This scenario covers the interactions between the actors of this use case in relation to the market.
Important aspects here are a distribution market where not only energy is sold, but also flexibility.
I.e. the charging station operator may include in the business model to sell flexibility while
maintaining the interests of his/her customers to charge vehicles when they are to be used. The DSO
can purchase such flexibility on the market or in a direct business relationship with the CSO to have
power quality management resources. The scenario also considers interactions with new energy
providers/aggregators that have local resources that should be utilized locally, e.g. for charging, or, in
combination with charging, to provide services towards the MV grid level.
The functions of the use case are depicted in Figure 82 based on the Smart Grid Architecture Model
(SGAM). Most functions are provided in the distribution domain to monitor and manage the Low
Voltage grid considering load and flexibility of EV charging processes. In the DER and Customer
Premise Domain exist local energy application controllers as well as monitoring (e.g. metering and
events by registering EVs) and actuation (start/stop charging, change charging intensity, …). In the
market zone the aggregation of LV grid energy resources (production, storage) and demand
resources provides a market to exchange such resources.
10.2.1.5 General Remarks
General Remarks
-
10.2.2 Diagrams of Use Case
Diagram of Use Case
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Secondary Substation
DSO
Local LV Grid
ressources (DER)
Private Charging Station
EVprivch
Public Charging Station
Cloud
NW1: Metering
NW2: Sub-station NW
NW3: Public IP Network
NW4: eCar
CommunicationNW4: eCar
Communication
NW5: Private IP Network
NW6: LV Grid Management Network
Private
Charging
SpotEVpubch
Public
Charging
Spot
NW7: DSO Network
Charging
Station
Controller
Public
Smart
Meter
Photovoltaic
Inverter
Battery
Inverter
Private
Smart
Meter
Energy
Management
Gateway
Metering
Head-end
System
Metering
Aggregation
(NNAP)
Low Voltage
Grid Controller
Meter Data
Management
System
Distribution
Management
System
(SCADA)
Information
Services
Market
(Distribution/Transport)
Charging
Station
Routing &
Reservation
Aggregated
Charging
Infrastructure
Management
Figure 75 Use case components and Networking Connectivity Options
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Energy
Providers
EV Owner/
Driver
Charging
Station
Operator
Reserve Charging
Space
Plug in/out EV
Negotiate energy
prices
Provide Charging Control
Directives (price motivation)
Provide Charging
Infrastructure
Provide Energy
Sell Energy
Manage Energy and
Power (Quality)<<include>>
Charge
DSO
<<
inclu
de
>>
<<in
clud
e>>
<<include>>
<<include>>
Metering<<
exte
nds>
>
<<include>>
<<include>>
E-mobility
Service
Operator Figure 76 - Use Case Diagram for EV charging scenario
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Availability
Check
Charging
Station
Routing &
Reservation
Charging
Station
Controller/
Gateway
Metering
Aggregation
Low Voltage
Grid Controller
Smart
MeterEVpubch
Charging
SpotEV Owner
/Driver
Energy
Providers
Find Charging Station with Context
Available Resources?
Available Power & Load ObjectivesAvailable Place, Energy (& Price)
Plugin & Context (SOC, Stay duration)
Reservation
Availability
Check
Market ConditionsNegotiate Price
Price Signals
Plugin & Context
Ideal Charging
Periods/Price
Signals
Planning
Planning &
Estimation
Start/Stop Charging
AP Update
...
...
Plugout
Metering Metering Data
Energy Consumption
Billing
Charging Opportunities
Start/Stop Charging
Available Power & Load Objectives
Available Power & Load Objectives
Available Resources? Current & Future
Demand, Flexibility
Planning
Start/Stop Charging
Start/Stop Charging
Aggregated
Charging
Infrastructure
Management
Available Resources? Current & Future
Demand, Flexibility
Figure 77 - Message Sequence Diagram for EV charging scenario
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Energy
Providers /
Aggregators
Charging
Station
Operator
Manage Power in Grid
(Plan & Control)
DER Owner
Battery (DER)
Owner
Provide Energy
Provide &
Plan Load
<<inclu
de>>
<<include>>
Consumers
Provide Load
Metering and Sensoring
<<include>>
DSO
Provide & Plan
Energy
<<include>>
<<
inclu
de
>>
Figure 78 - Use Case Diagram for energy and power management scenario
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LV Grid Mgmt.
Charging
Station
Controller/
Gateway
Low Voltage
Grid Controller
DSO
Photovoltaic
Inverter
Battery
InverterInformation
Services
GIS Data,
Operation
Objectives and
set-points
Monitoring &
Alarms
Data for
prediction
(Metering,
Weather)
Power & Energy
Control Loop
Metering
Aggregation
Production Now
Current and Planned State
(SoC, Charging, Providing)
Load & Production
Prediction
Available Resources? Current & Future Demand, Flexibility
Production Limits
Planning &
Estimation
Storage Control Objectives
Storage Control
Available Power & Load Objectives
Consumption Now
Planning & Control
DMS
(SCADA)
Figure 79 - Message Sequence Diagram for energy and power management scenario
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Energy
Providers/
Aggregators
Charging
Station
Operator
DER Owner
Battery (DER)
Owner
Generate &
Sell Energy
Sell Load Flexibility
<<inclu
de>>
Energy
Customers
Load
MeteringDSO
<<include>>
<<
inclu
de>
>
Buy Reserves for Balancing
EV Owner/
Driver
Sell Charging Service
Buy Charging Service
Buy Energy
<<include>>
<<include>>
Buy Energy
Figure 80 - Use Case Diagram for Energy Market scenario
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Sell Production
Meter Data
Management
DMS/
SCADA
Charging
Station
ControllerDSO ConsumerCharging
Station
Operator
Battery OwnerDER Owner
EV Owner/
Driver
Energy
Providers &
Aggregators
Market
(Distribution
/Transport)
Sell Decentralized
Energy Production
Sell Aggregated Energy
Production
Buy Energy & Demand Flexibility
Power/Energy Control Need
Sell Demand Flexibility
Sell Decentralized
Energy Production
Sell Decentralized
Energy Production
Sell Demand Flexibility
Billing
Billing
Billing
Negotiate Prices
Price Signals
Ideal Charging Periods/
Price Signals
DSO Demands
Sell Demand
Flexibility
Metering
CSO Demands
Price Signals
Billing
Billing
Aggregated
Charging
Infrastructure
Management
Figure 81 - Message Sequence Diagram for Energy Market Scenario
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Market
Enterprise
Operation
Station
Field
Process
Generation Transmission Distribution DER Customer
Premise
Low Voltage Grid
Control
Metering Production
Control
Home
Control
Actuation &
Monitoring
Actuation &
Monitoring
Actuation &
Monitoring
Metering
Aggegation
Information
Services
DMS
Transport & Distribution Market
Charging
Infrastructure
Management
Meter Data
Management
System
Charging
Station
Control
Charging Station Operation
Energy Provider / Aggregator
Figure 82 - SGAM Function Layer
Charging
Station
Controller
Metering
Aggregation
Low Voltage
Grid ControllerMDMEVpubch
PV
Inverter
Start/stop
charging
Metering Data Error
Get Consumption now
Data missing error
Get production now
MDM Error
Query MDM
Estimate load
Under
uncertainty
Reduced available power
Change
schedule
Figure 83 – AS3 Metering information interrupted
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Charging
Station
Controller
Low Voltage
Grid ControllerEVpubch
PV
Inverter
EV Owner
/Driver
Start/stop
charging
Heartbit
timeout
Schedule
With power
constraints
New reservation/plugin
Refuse temporarily (service
restricted)
Heartbit
Figure 84 – AS2 LVGC-CSO connection interrupted
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DSO
Charging
Station
ControllerLow voltage
grid controller
E-mobility
Service
Operator
Charging
Station
Routing &
Reservation
PS2.10
Charging
spot
PS2.6
PS1.8
PS 1.6, PS 1.9
PS1.6, PS1.9
PS 2.4
PS 2.9
DMS
PV Local
Production
Battery
Storage
PS
2.8
PS
2.7
PS1.
1, P
S1.
3
PS
1.2,
PS
1.5
Aggregator & CSO
PS
3.3
MarketPS3.5
PS
2.5
PS3.4
Meter
Meter Aggregation
PS 1.11
PS1.
11
PS
3.6
Aggregated
Charging
Infrastructure
Management
PS1.3
PS1.4, PS1.7
Figure 85: Diagram of the Interactions described in section 4.1
10.2.3 Technical Details
10.2.3.1 Actors: People, Systems, Applications, Databases, the Power System, and Other
Stakeholders
Actors
Grouping (Community) Group Description
Actor Name see Actor List
Actor Type see Actor List
Actor Description see Actor List
Further information
Components associated
Electrical Vehicle
Owner
Person The owner or user of an
electrical vehicle demanding
charging services.
Requests charging service
(demand, time window),
EV or Plug-In Hybrid
Electrical Vehicle
(PHEV)
-
Charging Station
Operator (CSO).
Role Operator of a Charging station
(which is an electrified parking
lot with several Charging Spots)
is an independent enterprise or
owned by Energy provider,
DSO, etc.
- it aggregates EV load, offers
demand flexibility.
- Builds and maintains the
- CS controller - Charging spots
(CS), sub-meters - Grid node/main
meter
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charging schedule for all EVs
connected to its charging spots
- Receives from DSO (LVGC)
actual and predicted available
power profile
- reports the EV load profile
- handles user payment for EV
services
- clearance with energy
provider or market
Every Charging station in a LV
grid, even from different CSOs,
becomes allocated an amount
of energy resources
proportionally to the number
of charging spots.
E-Mobility Service
Operator
Role - Lists the best charging station
locations to EVs,
- Handles reservations
- Receives from CSPs
availability updates
- May be owned by
charging station
operator.
- Reservation mgmt.
- Routing server
Distribution System
Operator (DSO)
Role - limits charging capacity of CS
- LVGC receives load max/min profile from primary station
- LVGC receives price information from
- LVGC calculates set points for aggregators, DG, storage
- LVGC/sec.station, - Primary station - Grid
Energy Provider Role - Provides energy to customers.
- Sends price signals, receives load information,
- May be an aggregator An Energy Provider may also be an actor aggregating many distributed energy resources.
Aggregator Role An entity able to aggregate
several production units as well
as demand flexibility. This
enables the aggregator to
operate on the market.
- May be an energy provider as well as provider of demand flexibility.
Consumer Person Other consumers in a LV grid
that provide loads and needs
to be considered in the
power/energy management
-
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views.
Battery (storage)
Owner
Role receives set points for Storage
charging and discharge from
DSO (LVGC)
- Fixed Storage, controller, meter
Charging Spot (CS) System - A dumb unit connecting an EV electrically to the grid via a plug. It is controlled by a home gateway/charging station controller.
-
Distributed Energy
Resource (DER)
System - receives set points from DSO (LVGC)
- reports generation
PV system, Wind mill
Inverter power Control,
meter
Meter Data
Management
System (MDMS)
System System for validating, storing,
processing and analyzing large
quantities of meter data.
-
Distribution Market System A market where it is possible to
buy and sell energy and
demand flexibility
-
Information Services System Commonly available services
provided by a third party. E.g.
weather information needed to
predict PV production.
-
Charging Station
Routing &
Reservation
System System including services for
EV owners to find charging
stations as well as for the
charging station operator to
manage several charging
stations.
-
Aggregated Charging
Infrastructure
Management
System System enabling to manage
several charging stations
providing interfaces to external
sub-systems (routing +
reservation), monitoring and
management of flexibility.
Operated by the CSO
Distribution
Management
System (DMS)
System Overall grid monitoring and
control system for the
distribution grid providing high
level control objectives
towards lower grid levels.
Part of the SCADA system of the DSO.
Metering Head-end
System (HES)
System Central component residing at
the DSO.
Provides interfaces towards
and MDM system.
-
Metering
Aggregation OR
System Local aggregation point OR
Neighbourhood Network
Ref: Smart Meters Co-ordination Group -
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NNAP Access Point (NNAP) is a
functional entity that provides
access to one or more LNAP’s,
metering end devices,
connected to the
neighbourhood network (NN).
Smart Metering Use Cases
Low Voltage Grid
Controller (LVGC)
System Local DSO driven controller
located in the secondary sub-
station.
The LVGC implements a Substation Control System.
Photovoltaic
inverter
System PV Inverter enabling to reduce
the production output to the
grid if strictly needed.
-
Battery Inverter System Battery Inverter also including
a control system to manage the
batteru charging/discharging.
In cases where a large storage
exist in the LV grid, this
inverter is usually providing
main control functions – e.g.
frequency stability control.
-
Charging Station
Controller
System A control box controlling when
charging spots can be activated
and at which charging speeds.
It plans charging in relation to
DSO’s and CSO’s requirements.
-
Energy Management
Gateway
System Same as charging station
controller. Only controls a few
charging spots. Is also
responsible for controlling
other in-household flexible
loads and production. It is also
known and referred to as a
Home Gateway due to its
capabilities for home
automation beyond energy
management.
This system implements the Customer Energy Management System.
EV System Electrical vehicle or Plug-In
Hybrid Electrical Vehicle (PHEV)
-
Smart Meter (SM)
System A smart meter providing
production and consumption
values. May also enable
advanced sensoring providing
active/reactive production,
frequency monitoring, voltage
-
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monitoring, etc.
10.2.3.2 Preconditions, Assumptions, Post condition, Events
Use Case Conditions
Actor/System/Information/Contract Triggering Event Pre-conditions Assumption
Charging Station Infrastructure
Management
It serves several charging stations and
their CSOs for instance redirects
reservation requests from traveling EV
users to free charging stations. This
actor is optional, a simpler approach
would be to find charging stations as
POI using the navigation system (but
without knowing their availability)
Reservation in PS1
It is assumed for now that reservation
is done without any commitment or
payment
User registration, payment in PS1
It is important that any EV owner
receives service, even she is not
registered at a certain CSO or system
wide (openness). Since a full charging
costs about 3-4€ and parking in the
same order, we recommend simpler
prepaid approach. However payment
is not considered here in detail.
10.2.3.3 References /Issues
References
No. References Type Referen
ce
Status Impact on Use Case Originator/Or
ganisation
Link
1 EV Communication
Standard
DTS/IT
S-
00100
31
V0.0.1
Prelimina
ry draft
Communication ETSI ETSI ITS
WG1
2 ISO/IEC 15118
Road vehicles –
Communication
protocol between
electric vehicles and
grid
IEC
15118
Final Describes the
interface between an
electric vehicle and
the charging spot
including securit
IEC
3 Standard
IEC
62196
(1-3)
1- Final
3 – exp.
Dec 13.
Standard for electrical
connectors and
charging modes for
electrical vehicles.
IEC IEC
4 E-Mobility Use cases Work in
progress
E- Mobility co-
ordination group (EM-
CEN- http://e
mic-
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CG),
SG-CG/M490 smart
grids
CENELEC bg.org/fi
les/plugi
n-
index.pd
f
10.2.3.4 Further Information to the Use Case for Classification / Mapping
Classification Information
Relation to Other Use Cases
Will be a sub-use case of the generic Low Voltage grid use-case. Will share functions with the house-
hold use case as these operate in the same domain.
Level of Depth
High Level
Prioritisation
Under conditions of large penetration of electrical vehicles (pure as well as plug-in hybrids)
management of charging is needed unless large investments in grid reinforcements are made. The EV
control will provide an interesting new resource for demand flexibility due to the ability of absorbing
large quantities of energy as well as high flexibility in consumption.
Generic, Regional or National Relation
Generic
View
Technical, partially market options
Further Keywords for Classification
Electrical Vehicle Charging, Demand Flexibility, Low Voltage Grid Management, Aggregator Role,
Charging Station Operator.
10.2.4 Step by Step Analysis of Use Case
Scenario Conditions
No. Scenario
Primary
Actor(s)
Triggering Event Pre-Condition Post-Condition
PS1 EV Charging EV owner EV owner seeks a
charging station
EV and owner are valid
(credentials).
EV owner has a valid
reservation at a certain
charging station, has travelled
there and successfully received
desired charge.
PS2 Energy &
Power
Manageme
nt
DSO Periodical update or
dramatic change in
available power
resources
Data Links are OK,
agreements exist with
charging station
operator and energy
resource providers to
enable control.
No alarms, i.e. the grid power
quality is maintained and
energy resources are available
for future power management.
PS3 Energy
Market
Energy
Providers,
Aggregators
Periodic, based on
types of market
Established business
relations between
primary actors and a
Price agreements and billing
closed.
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Scenario Conditions
No. Scenario
Primary
Actor(s)
Triggering Event Pre-Condition Post-Condition
and CSO market platform
AS1 Plugged in
Charging
aborted
EV owner Plugin Event Reservation OK Av. Power alarm, no or
partial charging, plugout, leave
AS2 EV demand
control
disrupted
CSO Detection of Comm.
failure
Data flow LVGC CSO
interrupted
Schedule with reduced load
until the condition ends
AS3 Metering
Data flow
disrupted
DSO
(LVGC)
Detection of
missing data
Grid state is OK Conservative Available
Power estimates are
distributed until the
condition ends
10.2.4.1 Steps – Normal
For a better understanding of the following steps, the main interactions are depicted in Figure 85.
Scenario (see Figure 76 & Figure 77, Figure 11)
Scenario PS1: EV Charging
Step
No.
Event Name of
Process/
Activity
Description of
Process/Activity
Service Information
Producer
(Actor)
Information
Receiver
(Actor)
Information
Exchanged
Technic
al
Require
ments
R-ID
PS1.1 Charging
Station
Lookup
Find Charging
Station
Identify charging
station and
provide user
context
(expected stay
duration, needed
charge, …)
Optional EV Owner
+ EV
Charging
Station
Routing
Charging
Context.
PS1.2 Availability
Check
Availability
Check and
Response
The Charging
Station
Infrastructure
Mgmt. identifies
charging station
options and
informs EV
Owner.
Optional Charging
Station
Routing
EV Owner Available
charging
opportuniti
es.
PS1.3 Reservatio
n
Charging
Station
Routing
receives
reservation
request and
EV user selects
charging station,
arrival time
energy demand.
May get
additional
Optional EV Owner
+ EV
Charging
Station
Controller
Reserve
message
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redirects it to
CSO
information such
as routing advice.
PS1.4 Process
Reservatio
n
Reservation
handling at the
charging
station
Update Schedule,
allocate
resources
Charging
Station
Controller
Charging
station
Routing
Schedule
update and
resource
availability
PS1.5 Reservatio
n
successful
CSO returns
OK
OK response.
Charging station
Routing updates
its CS availability
list
Optional Charging
Station
Controller
EV Owner Reservatio
n
confirmatio
n
PS1.6 Plugin EV Plugin An EV plugs into
the Charging Spot
and provides
additional/updat
ed context
information
EV Charging
Station
Controller/
Gateway
Updated
Charging
Context.
PS1.7 Plugin
Handling
Re-planning of
resources
The Charging
Station Controller
(re-)/plans the (if
needed) charging
plan
Charging
Station
Controller
Charging
Station
Routing
Schedule
update and
Resource
availability
PS1.8 Start/Stop
Charging,
Change
Charging
Speed
Charging
Process
Management
The charging
station controller
starts/stops
charging as well
as manages
charging speed
Charging
Station
Controller
EV Start/Stop
commands.
Updated
charging
speeds.
PS1.9 Plug-out EV Plugout The EV plugs out
of the Charging
Spot. The
Charging Station
Controller
adapts.
EV Charging
Station
Controller
Plug-out
event
PS1.1
0
Periodic Metering Send charging
metering data to
meter
aggregation
system for billing
purposes
Smart
Meter
Meter
aggregatio
n
Meter data
PS
1.11
Periodic Metering Read meters for
state estimation
Meter
Aggregatio
n
LVGC Relevant
Meter Data
Scenario (see Figure 79 & Figure 80)
Scenario PS2: Energy Balancing& Power Management
Ste
p
No.
Event Name of
Process/Activit
y
Description of
Process/Activity
Servic
e
Informati
on
Produce
r (Actor)
Information
Receiver (Actor)
Information
Exchanged
Technic
al
Require
ments R-
ID
- Update Provide update The DMS provides DMS LVGC - Setpoints
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LVGC
operatio
n
of the LVGC
operation
settings
information to the
LVGC to update high-
level operation
objectives as well as
changes in data
models such as grid
topology information,
newly connected
charging stations etc.
- Settings
- Data
models (e.g.
grid
topology)
- Update
LVGC
predictio
n
informati
on
Provide update
of the LVGC
data for
prediction
Information is pushed
(or pulled) from
information services
that are useful in the
LV grid management
operation such as
weather data.
Informa
tion
Services
LVGC - Weather
data
- Expected
load profiles
- …
2.1 Periodic Load and
Production
Prediction
The LVGC predicts the
expected production
and load a predefined
time into the future
for planning purposes
LVGC LVGC Updated
prediction
profiles
2.2 Periodic Metering Current load in
different busses of
the LV grid
Meterin
g
Aggrega
tion
LVGC Load
information
on busses
2.3 Periodic Distributed
Generation
Current generated
power in different
busses of the LV grid
Meterin
g
Aggrega
tion
LVGC Generated
information
on busses
2.4 Periodic Set Available power
for EV charging to all
charging stations
LVGC Charging
Station
controller
Available
power
profile
2.5 Periodic Control
Re-planning
The LVGC plans the
local power and
energy resources to
maintain service
quality within
acceptable limits. It
may perform this
planning based on
setpoints from the
MV level.
LVGC LVGC Power and
Energy
control plan
in the LV
grid.
2.6 Periodic Charging Load
profile update
CSO updates the
schedule considering
the preferred loads
from aggregator and
the CSO available
power constraints
Chargin
g
Station
Controll
er
LVGC EV Loads
update
2.7 Overvolt
age/Curr
ent
Limit
Production
If overvoltage/
over-current events
occur the LVGC can
choose to limit the
production in critical
LVGC Photovoltaic
Inverter
Production
Limits
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periods to maintain
power quality.
2.8 Service
quality
deviation
s
Change battery
control
objectives
A local battery in the
grid can be requested
to change its
objectives to
increase/decrease
load to aid in the
operational
parameters
LVGC Battery Inverter Setpoints/o
bjectives for
battery
control
2.9 Power
quality
deviation
s
Change
demand
objectives
The LVGC can request
flexibility services
from the Charging
Station Controller to
increase/decrease
load now and in the
future. This involves
hard constraints on
power availability.
LVGC Charging
Station
Controller
Setpoints/o
bjectives for
-charging
demand
flexibility
- Available
power
profile
2.1
0
Events/A
larms
Monitoring
events/Alarms
A monitoring event or
alarm (depending on
criticality level) is
raised and sent to the
DMS to report about
the current and past
state of the LV grid.
LVGC DMS Event/Alar
m
Scenario (see Figure 80 & Figure 81)
Scenario: PS3: Energy Market
Step
No.
Event Name of
Process/Activi
ty
Description of
Process/Activity
Se
rvi
ce
Information
Producer
(Actor)
Information
Receiver
(Actor)
Information
Exchanged
Techni
cal
Requir
ement
s R-ID
3.1 Periodic Sell
Production
Local energy sources
(storage and production)
sell energy resources to
an aggregator.
DER/Battery
owner
Aggregator Energy
production
capabilities
3.2 Periodic Sell
Aggregated
Production
Local energy resources
across several LV/MV
grids are aggregated
enabling the aggregator
to act on the retail
market
Aggregator Market Aggregated
energy
production
capabilities
3.3 Periodic Provide
EV charging
demand
The charging station
forwards an already price
optimized demand curve.
CSO EV
Aggregator
(retailer)
demand +
flexibility
capabilities
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(alternatively, it forwards
the demand plus its
flexibility and the
aggregator performs the
price optimization)
3.4 Periodic Price signals pricing information is
provided to energy
providers/aggregators.
Market EV
Aggregator
Price signals
3.6 Periodic Price signals The CSO uses the price
information and the
flexibility of the charging
operation to find an
optimal demand curve
EV
Aggregator
CSO Price signals
3.5 Periodic Price
Optimized
Energy buying
The aggregator buys
updates the energy need
by buying on the intraday
market
EV
Aggregator
Market Demand
10.2.4.2 Steps – Alternative, Error Management, and/or Maintenance/Backup Scenario
Scenario
Scenario (Sub-
scenario)
AS2: EV demand control disrupted
Step
No.
Event Name of
Process/Activity
Description of
Process/Activity
Service Information
Producer
Information
Receiver
Information
Exchanged
Technical
Requirements
R-ID
1 LVGC CS
connection
lost
Scheduling
under av.
power
uncertainty
Enter
precautious
mode.
Refuse new
requests
CSO Charging
Spots
reduced
charging
duration
Scenario
Scenario (Sub-
scenario)
AS3: Metering data flow disrupted
Step
No.
Event Name of
Process/Activity
Description of
Process/Activity
Service Information
Producer
Information
Receiver
Information
Exchanged
Technical
Requirements
R-ID
1 consumption
Metering
samples
missing
Estimate
load under
uncertainity
Conservative
calculation of
available
power
CHANGE LVGC CS
controller
Reduced
Available
power
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10.2.5 Information Exchanged
Information Exchanged
Name of Information
Exchanged
Description of Information Exchanged Requirements to information data R-ID
Reservation Information from vehicle: arrival, expected
departure time, min charging energy, maximum
energy,
Available power Calculation of maximum power that can be
pulled out from a node for charging
Charging load profile Aggregated load profile (plan) for a charging
station
Metered Consumption bus load Aggregated domestic load metered in one
period
Metered Generation power Aggregated bus gen .power in one metering
period
Generation output limitation Control signal to the PV inverted 0<c<=1
Charging start/Stop Sub-meter on/off signal
10.2.6 Common Terms and Definitions
Common Terms and Definitions
Term Definition
LVGC Low voltage grid controller
CS Charging spot
EV Electric vehicle
CSO Charging station operator (controls EV parking with several CPs), aggregates EV load, is owned by Energy
provider or charging station infrastructure provider
Routing Pre-charging User Service to find the best CS
EV demand Amount of energy required by an EV
Plugin event User is at CP and plugs in charging (and data) cable
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10.3 USE CASE NAME: External generation site
10.3.1 Description of the Use Case
10.3.1.1 Name of Use Case
Use Case Identification
ID Domain(s)
Name of Use Case
External Generation Site
10.3.1.2 Version Management
Version Management
Changes /
Version
Date Name
Author(s) or Committee
Domain
Expert
Area of
Expertise /
Domain /
Role
Title Approval
Status draft, for comments,
for voting, final
0.00 25.01.2013 Rasmus Løvenstein Olsen,
Florin Iov, Jayakrishnan
Radhakrishna Pillai, Rafael
Wisniewski, Christoffer Sloth
draft
0.3 18.02.2013
0.4 10.03.2013 Update
0.5 18.03.2013 Update
0.8 19.07.2013 Rasmus Løvenstein Olsen,
Christoffer Sloth, Florin Iov
Update
10.3.1.3 Scope and Objectives of Use Case
Scope and Objectives od Use Case
Related business case Use case 2: Self-Optimized Low Voltage Grid Domain
Scope With the anticipated increase in small decentralized energy resources from
primary wind and photovoltaic (PV), the low voltage (LV) grids are exposed
to new load scenarios than originally designed for. Further, new high
consumer demands from Electrical Vehicle (EV) mobility and heat pumps
challenge existing LV grid infrastructures additionally. As a result, there is an
increased interest in technologies to improve the LV grid operation. These
mainly entail: local energy storage, active control of energy fed in electrical
grid, flexible demand control (entailing both end-user managed demand
response and autonomic demand control) for house-holds and EVs. This use
case covers the automation and control techniques required for future LV
grids and enables the DSO to utilize the flexibility of the LV grid assets.
The reference scenario for this use case consists of a MV and LV grid
containing: 1) fixed and shift-able energy consumption from households,
small enterprises and EVs, 2) production from PVs and wind turbines, 3)
Energy storage. Hierarchical controller architecture is utilized, where a
distribution management system (DMS) is at the upper most level. This
provides commands to the MV grid controller, which sends commands to
the LV grid controllers as well as flexible generation and consumption in the
MV grid. Finally, the LV grid controller sends commands to flexible assets in
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the LV grid. The LV grids are connected to the MV grid via a controllable
transformer station with an online tap changer (OLTC).
It is considered that all components in the architecture are connected with a
communication network providing monitoring data from and control of the
individual components. The LV grid implements its own control mechanisms
which are responsible for: a) maintaining an acceptable voltage profile,
security and safety, b) balancing available power resources (energy storage
and generation) with the (flexible) demand, and c) handling the interactions
between a) and b). The control infrastructure is managed by one or more
dedicated LV grid controllers which provide functionality to support the sub-
use cases introduced in the following sections. This Use Case is considering
only faults and performance degradation within the public communication
network, and the system’s overall ability to perform normal grid operation
even during network faults and performance degradation.
Objective The objective is to demonstrate the feasibility of distribution grid operation
over an imperfect communication network
10.3.1.4 Narrative of Use Case
Narrative of Use Case
Short description – max 3 sentences
The Use Case is focusing on demonstrating the feasibility of controlling flexible loads and renewable
energy resources in LV grids over an imperfect communication network. Flexibility of LV grids for
upper hierarchical control levels is also investigated
Complete description
With the introduction of significant decentralized energy production from wind and photovoltaic
plants in the LV grid along with energy storage as illustrated in Figure 86, new problems arise. In this
setting the low voltage grid control should preferably be able to: 1) control the voltage profile along
the low voltage feeders, 2) optimize MV grid losses; 3) optimize energy cost; 4) aggregate the
flexibility of LV and MV assets that can be used as an input to the MV control and distribution
management system (DMS). The grid operation should in this matter be resilient to faults and
performance degradation in the public communication lines between the low voltage grid controller
and the assets in the electrical grid with special focus on the low voltage side, hereby limiting the
effect of changing network conditions on the electrical grid performance. This means that the use
case also includes mechanisms for adapting the communication to events in the network that
challenge the communication and the quality of the data exchanged between the controlled and
controlling entities.
Under these settings, two main scenarios are defined as to show the above characteristics:
- Technical flexibility and performance: Resilience of control towards faults and congestions in
communication networks.
- Commercial feasibility and flexibility: Aggregation of generation and demand (abstraction of
models).
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Primary Substation
Automation&Control
MVGC
ProsumerLarge DER Large DER
HV Grid
HV
MV
MV
LV
Prosumer
Consumer
Interm. DER
Consumer
MicroDER
SME
Farm
SME
EnergyStorage
…
MV
LV
...
...
...
...
MV
LV
Use Case 2.3
Prosumer
Retailers
DMS
TSO
ForecastProviders
Markets
AggregatorsMV/LV
WAN
AN
Technical Flexibility
&Performance
Commercial Feasibility
& Flexibility
AN Provider(s)
AN Provider(s)
WAN Provider(s)
Secondary Substation
Automation&Control
Secondary Substation
Automation&Control
Secondary SubstationAutomation & Control
LVGC
Figure 86 Overview of Use Case
10.3.1.5 General Remarks
General Remarks
The definitions for distributed energy resources used for this Use Case are defined in the table
below. These definitions are taken into account the voltage and current at the connection point as
well as the power rating of the device.
DER Definition Voltage
Ratings
[kV]
Current
Ratings
[A]
Installed
Capacity
[kW]
DER Type
Micro DER < 1 <16 < 5 DER at Household level
e.g. micro CHP, PV
system, wind turbine,
energy storage,
Intermediate DER < 1 > 16 5 < …< 500 DER connected to low
voltage feeders.
Examples: standalone
systems e.g. PV panels
and heat pumps, single
wind turbine, battery
storage, charging spot for
EVs, etc
Large DER > 1 > 16 > 500 DER connected to
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medium voltage grids.
Examples: wind or PV
power plants, Combined
Heat and Power plants,
Supermarkets with
refrigeration systems and
charging stations for EVs,
etc.
10.3.2 Diagrams of Use Case
Diagram of Use Case
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Market(s)
Data Transport(WAN)
Data Transport(AN)
Control of assets
Retailer
DSO
TSO
ForecastProvider(s)
AggregatorTechnical (MV/LV)
Medium Voltage Grid Controller
Low Voltage Grid Controller
Prosumer
Consumer
Micro DER
WAN Provider(s)
Network
performance
change
Network
congestion
Lost network
connectivity
Network
performance
change
Intermediate DER
Large DER
DMS
AN Provider(s)
ProsumerNetwork
congestion
Lost
Network
connectivity
Figure 87 Overview of use cases
The use cases as defined in the following document will be running on top of a system described in
slightly more details in the following using SGAM depicturing methodology.
Based on SGAM Framework the component layer of the Use Case is shown in Figure 88. In the
following a brief overview of the architecture and functionality of the use case diagram is provided in
component and functional layers as described in [UCC]. This approach describes the relation
between components and functions in terms of electrical grid components (x-axis) and zones of
operation (y-axis) which is helpful also to understand the need for communication between the
various components and functions. This shows the generic interaction between assets and
controllers for the Control of Assets use case.
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Component Layer
TSO
AN NetworkProvider(s)
MV grid control
RetailerForecast Provider
TechnicalAggregation (LV)
LV grid control
Large DER
DMS
TechnicalAggregation
(MV)
WAN NetworkProvider(s)
Markets
Prosumer Micro DER ConsumerIntermediat
e DERProsumer
Smart Meter
Smart Meter
Smart Meter
Smart Meter
MV Grid Components
LV Grid Components
Station
Distribution DER Customer PremisesTransmission
Field
Process
Operation
Enterprise
MarketWAN Channel(s)
Private Channel(s)
AN Channel(s)
Figure 88 Set of physical components and their locations in the smart grid setup
Communication layer of the Use Case describing different potential communication technologies
between various components is given in Figure 89. Faults and errors causes performance
degradation that needs to be taken into account, which creates the error scenarios for the Data
Transport use cases at Access Network and Wide Area Network level.
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TSO
AN NetworkProvider(s)
MV grid control
RetailerForecast Provider
TechnicalAggregation (LV)
LV grid control
Large DER
DMS
TechnicalAggregation
(MV)
WAN NetworkProvider(s)
Markets
Prosumer Micro DER ConsumerIntermediat
e DERProsumer
Smart Meter
Smart Meter
Smart Meter
Smart Meter
MV Grid Components
LV Grid Components
Station
Distribution DER Customer PremisesTransmission
Field
Process
Operation
Enterprise
Market
Public internet
xDSL, Fiber, Cable, UMTS, WiMAX
Private net
Fiber, Ethernet, ATM
Private net
PLC,Fiber,
Ethernet, ATM
Private net
PLC,Fiber,
Ethernet, AT, TETRA
Public internet
xDSL, Fiber, Cable, UMTS, WiMAX
Public Access Networks
xDSL, Cellular (UMTS, GPRS), WiMAX, PLC
Site comm.
WLAN, Ethernet, WB-PLC,
Zigbee, Z-wave
Communication Layer
Figure 89 Different communication means used for the various components to interact with each other
Functionalities in the grid that allows the operation and the two cases; commercial and technical
flexibility scenarios. These are connected with the communication lines as shown above, and is
executed on the various grid components as illustrated in Figure 88.
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TSO
AN NetworkProvider(s)
MV grid control
RetailerForecast Provider
TechnicalAggregation (LV)
LV grid control
Large DER
DMS
TechnicalAggregation
(MV)
WAN NetworkProvider(s)
Markets
Prosumer Micro DER ConsumerIntermediat
e DERProsumer
Smart Meter
Smart Meter
Smart Meter
Smart Meter
MV Grid Components
LV Grid Components
Station
Distribution DER Customer PremisesTransmission
Field
Process
Operation
Enterprise
Market Market prices
Weather
information
Commercial
aggregation
HV grid management,
GIS system data,
planning tools,
visualisation
MV/LV grid
management, GIS
system data, planning
tools,
visualisation
Technical aggregation
Grid resynch., fault detection and
isolation, demand side mngt and
response, curtailment, ancillery services
Protection and monitoring
Warnings and alarms for
grid failure
Actuation Actuation Actuation
Protection and metering
Functional Layer
Figure 90 Different functionalities used in the system in order to be able to execute the use cases over the
network on the different physical components
In the following part of this document, high level descriptions of the use cases, step by step, will be
done.
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10.3.3 Technical Details
10.3.3.1 Actors: People, Systems, Applications, Databases, the Power System, and Other
Stakeholders
Actors
Grouping (Community) Group Description
Actor Name see Actor List
Actor Type see Actor List
Actor Description see Actor List
Further information
specific to this Use Case
Micro DER Distributed energy resources at house hold
level. Examples of such resources are: wind
turbine, PV system, micro CHP, energy
storage, EVs, etc
Intermediate DER Distributed energy resources connected to
low voltage feeders. Examples of such
resources are: standalone systems e.g. PV
panels and heat pumps, single wind turbine,
energy storage, charging spot for EVs, etc.
Entities connected to the LV
grid, but not belonging to
households or small
enterprises
Large DER Distributed energy resources connected to medium voltage grids. Examples of such resources are: wind and PV power plants, Combined Heat and Power plants, Supermarkets with refrigeration systems and charging stations for EVs, etc.
Consumers Role Consumers that are not offering flexibility in
operation and control such as: households,
small enterprises
Prosumers Role Consumers that are offering flexibility in operation and control. They can be connected at LV or MV grids and can contain micro, intermediate, or large DER.
Smart household or small
enterprise
Smart Meter (SM) System The metering end device is a combination of the following meter-related functions from the Smart Metering reference architecture: • Metrology functions including the conventional meter display (register or index) that are under legal metrological control. When under metrological control, these functions shall meet the essential requirements of the MID; • One or more additional functions not covered by the MID. These may also make use of the display; • Meter communication functions.
Every household is equipped
with a smart meter.
Comm. Network Provider Role Provides communication services to the
system, e.g. M2M infrastructure.
Distribution System Operator (DSO)
Role
According to the Article 2.6 of the Directive: "a natural or legal person responsible for operating, ensuring the maintenance of and, if necessary, developing the distribution system in a given area and, where applicable, its interconnections with other systems and for ensuring the long-term ability of the system to meet reasonable demands for the distribution of electricity". Moreover, the DSO is responsible for regional grid access and grid stability, integration of renewables at the distribution level and regional load balancing.
Utility companies
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Transmission System Operator (TSO)
Role
According to the Article 2.4 of the Electricity Directive 2009/72/EC (Directive): "a natural or legal person responsible for operating, ensuring the maintenance of and, if necessary, developing the transmission system in a given area and, where applicable, its interconnections with other systems, and for ensuring the long-term ability of the system to meet reasonable demands for the transmission of electricity". Moreover, the TSO is responsible for connection of all grid users at the transmission level and connection of the DSOs within the TSO control area.
Transmission system
operator(s)
Technical Aggregators MV/LV Role Offers services to aggregate signals/information regarding flexibility of different consumers and prosumers from MV and LV grids respectively. This aggregated information is used by hierarchical control levels.
Retailer Role Entity selling electrical energy to consumers - could also be a grid user who has a grid connection and access contract with the TSO or DSO. In addition, multiple combinations of different grid user groups (e.g. those grid users that do both consume and produce electricity) exist. In the remainder of this document, the terms customer/consumer and grid user are used interchangeably where appropriate.
Markets Market for trading energy and ancillary
services
Power, Energy, Ancillary
Services
Forecast Provider System Compute forecast for consumption and renewable generation in a given area based on weather forecast, historical data, etc.
May be separate for wind,
Solar Irradiance, consumption,
etc.
Low Voltage Grid Controller
System System placed in the secondary substation aiming to control assets on LV feeders and provide flexibility to upper control levels.
Medium Voltage Grid Controller
System System placed in the primary substation aiming to control assets on MV feeders and provide flexibility to TSO and DMS.
LV Grid Components System Grid components such as transformers, cables, breakers, etc.
MV Grid Components System Grid components such as transformers, cables, breakers, etc.
Distribution Management System
System A system which provides application to monitor and control a distribution grid from a centralized location, typically a control centre
10.3.3.2 Preconditions, Assumptions, Post condition, Events
Use Case Conditions
Actor/System/Information/Contract Triggering Event Pre-conditions Assumption
AN/WAN between communicating
entities (MVGC, LVGC and Assets)
Change in network
performance (no-congestion)
“Normal” cross
traffic patterns in
network
-Bidirectional communication with
consumers can be done for effective
network reconfiguration.
-Traffic increase is caused by external
factors, i.e. uncorrelated with the
control traffic.
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AN/WAN between communicating
entities (MVGC, LVGC and Assets)
Congestion in network High load network
condition
- Bidirectional communication with
consumers can be done for effective
network reconfiguration.
- Some QoS configuration possibilities
exists
-Traffic increase is caused by external
factors, i.e. uncorrelated with the
control traffic.
AN
Wired/wireless network
Network connection is lost Pre-existent
connection at
network layer
- Requires a notion of logic
connectivity between entities at
network layer.
- The cause of lost connectivity is in
the network (i.e. we delimit from non-
responsive devices/crashed devices).
AN
Wireless networks
Link conditions changed “Normal” channel
condition
- Some link reconfiguration
possibilities exists and is accessible
- Bidirectional communication with
consumers can be done for effective
network reconfiguration.
- Change of channel conditions are
uncorrelated with the power grid and
happen at random time intervals.
AN
Wireless networks
Link capacity reached High load on AN - Some QoS options exists for
reconfiguration of the link
- Bidirectional communication with
consumers can be done for effective
network reconfiguration.
- Factor that triggers the congestion
state is not correlated with the control
system, e.g. too many customers in
the network
AN
Wireless networks
Link connection is lost Pre-existent
connection at link
layer
- Bidirectional communication with
consumers can be done for effective
network reconfiguration.
- Alternative AN’s are available.
10.3.3.3 References /Issues
References
No. References Type Reference Status Impact on
Use Case
Originator/Organisation Link
1 Public SG-CG/M490/C
Smart GridReference
Architecture
V 3.0
2 Public
10.3.3.4 Further Information to the Use Case for Classification / Mapping
Classification Information
Relation to Other Use Cases This sub-use case must exploit the flexibility offered in sub-use cases 1 and 2 in the low voltage grid controller.
Level of Depth
High level description
Prioritisation
High/Mandatory
Generic, Regional or National Relation
Regional
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View
Technical
Further Keywords for Classification
Smart grid control, network failure resilience
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10.3.4 Step by Step Analysis of Use Case
Scenario Conditions
No. Scenario
Name
Primary
Actor
Triggering Event Pre-Condition Post-Condition
4.1 Base Case WAN/ANPro
vider
No events in WAN/AN Normal Operation Normal operation
4.2 Network
Performanc
e Changed
WAN/ANPro
vider
Change in network
performance
Normal Operation
4.3 Network
Congestion
WAN/AN
Provider
Congestion in network Normal Operation Congestion
4.4 Lost
Network
Connectivit
y
WAN/AN
Provider
Network connection is lost Normal Operation Loss of connectivity
Each of these scenarios is considering three subcases as:
Energy balance – where the operation of MV grids is targeted. LV grids are considered aggregated and the LVGC is offering flexibility to MVGC. Thus MVCG is primarly controlling the assets such as Large DER, prosumers and LV grid via LVGC to keep the energy balance. The primary actor involved here is the WAN Provider
MV control – where the focus is to control the voltage profile on MV grids using reactive power capabilities offered by Large DER, MV prosumers and the secondary substations on MV side. The primary actor involved here is the WAN Provider
LV control - where the focus is to control the voltage profile on LV grids using reactive power capabilities offered by Micro and Intermediate DER, flexible consumption and production at household or small and medium enterprises. The primary actor involved here is the AN Provider(s)
These subcases may involve only some of the actors while other are neglected as mentioned above.
10.3.4.1 Steps – Normal
Grid operations
In normal operation the grid is operated as follows. Starting from the lowest level (right in the
figure), consumers and DERs sent measurements to the LV grid controller and receive setpoints from
the LV grid controller. The measurements from LV assets are aggregated before they are sent to the
MV grid controller. Similarly, the LV grid control receives an aggregated setpoint from the MV grid
controller that must be dispatched to the individual LV assets. The MV grid controller communicates
with Large DERs and LV grid controllers to exchange aggregated flexibility, measurements, and
setpoints. Additionally, the MV grid controller sends the aggregated flexibility to the DMS, which
generates setpoints based on the available flexibility, weather information, and market conditions.
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TSOAN NetworkProvider(s)
MV grid controlRetailer
Forecast ProviderTechnical
Aggregation (LV)
LV grid control
Individual setpoints (MV)
Individual setpoints
Large DERMicro DER/
Intermediate DER/Prosumer
Consumer
Measurements
Aggregated flexibility (LV)
Measurements
Aggregated set point
AggregatedFlexibility (LV)
DMS
Weather information
Setpoint
Aggregated flexibility (MV)
Aggregated Setpoint (MV)
Measurements
Measurements
Measurements
NetworkStatus/
performance
Aggregated set point
Individual setpoints
TechnicalAggregation (MV)
AggregatedFlexibility (MV)
Measurements
WAN NetworkProvider(s)
Markets
Price signal
Aggregated setpoint (MV)
NetworkStatus/
performance
Individual
setpoints (MV)
Individual setpoints
Aggregated flexibility (LV)
Individual setpoints (MV)
Measurements
Aggregated flexibility (MV)
Weather information
Bids
Accepted bids
Setpoints
Measurements
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
Scenario
Scenario
Name :
Base Case
Step
No.
Event Name of
Process/Activ
ity
Description of
Process/Activit
y
Servic
e
Information
Producer
Information
Receiver
Information
Exchanged
Technical
Requiremen
ts R-ID
1 Periodica
lly
Status and
measurement
collection
Data regarding
status of the grid
is collected and
other information
such as wind
GET MV grid
controller, grid
sensors, smart
meters, grid
components
Technical
aggregator, LV
grid controller,
MV/LV grid
management
Grid status
data (Voltage,
frequency, …)
2 Periodica
lly
Actuation
calculations
Determine
response to
demand/supply
EXECU
TE/SET
Technical
Aggregator, LV
grid controller
Actuators, LV
grid controller
Actuation
signals,
reference
signal to LV
grid
controller
10.3.4.2 Steps – Alternative, Error Management, and/or Maintenance/Backup Scenario
Change in network performance
This scenario deals with time varying performance in the network, and the adaptation of access methods to provide reliable data exchange between entities communicating.
Scenario
Scenario Name : Network performance change
Step
No.
Event Name of
Process/Activit
y
Description
of
Process/Act
Service Information
Producer
(Actor)
Information
Receiver
(Actor)
Information
Exchanged
Technical
Requiremen
ts R-ID
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ivity
1 Change in
network
performanc
e (no-
congestion
Network
monitoring;
access adaptation
mechanisms
Monitoring of
network
performance
leads to
detection of
performance
loss
GET Communicati
on Network
Provider
Monitoring Potentially
network
performance
measurement
data, and signal
to controller
2 Change and
recalculation
of access
reconfigurati
on
parameters
EXECUTE Monitoring Information
access manager
Access
configuration
parameters
* This scenario is relevant for both WAN and AN.
TSOAN NetworkProvider(s)
MV grid controlRetailer
Forecast ProviderTechnical
Aggregation (LV)
LV grid control
Individual setpoints (MV)
Large DERMicro DER/
Intermediate DER/Prosumer
Consumer
Measurements
Aggregated flexibility (LV)
Aggregated set point
AggregatedFlexibility (LV)
DMS
Weather information
Setpoint
Aggregated flexibility (MV)
Aggregated Setpoint (MV)
Measurements
Measurements
NetworkStatus/
performance
Aggregated set point
Individual setpoints
TechnicalAggregation (MV)
AggregatedFlexibility (MV)
Measurements
WAN NetworkProvider(s)
Markets
Price signal
Aggregated setpoint (MV)
NetworkStatus/
performance
Individual setpoints
Aggregated flexibility (LV)
Individual setpoints (MV)
Measurements
Aggregated flexibility (MV)
Weather information
Bids
Accepted bids
Setpoints
Measurements
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
Aceessreconfiguration
Aceessreconfiguration
AN network condition change
AN network condition change
WAN network condition change
Aceessreconfiguration
Aceessreconfiguration
WAN network condition change
Aceessreconfiguration
Congestion in network
This scenario deals with more severe network conditions, i.e. congestions in the network, and the adaptation of access methods to provide reliable data exchange between entities communicating.
Scenario
Scenario Name : Congestion in network detected
Step
No.
Event Name of
Process/Activit
y
Description
of
Process/Act
ivity
Service Information
Producer
(Actor)
Information
Receiver
(Actor)
Information
Exchanged
Technical
Requiremen
ts R-ID
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1 Network
congestion
detected
Network
monitoring;
access adaptation
mechanisms
Monitoring of
network
performance
leads to
detection of
performance
loss
GET Communicati
on Network
Provider
Monitoring Potentially
network
performance
measurement
data, and signal
to controller
2 QoS/network
option
availability
and
reconfigurati
on
GET/EXE
CUTE
Communicati
on Network
Provider
Communication
Network
Provider
QoS parameter
settings
3 Change and
recalculation
of access
reconfigurati
on
parameters
EXECUTE Monitoring Information
access manager
Access
configuration
parameters
*NB This scenario is relevant for both WAN and AN
TSOAN NetworkProvider(s)
MV grid controlRetailer
Forecast ProviderTechnical
Aggregation (LV)
LV grid control
Individual setpoints (MV)
Large DERMicro DER/
Intermediate DER/Prosumer
Consumer
Measurements
Aggregated flexibility (LV)
Aggregated set point
AggregatedFlexibility (LV)
DMS
Weather information
Setpoint
Aggregated flexibility (MV)
Aggregated Setpoint (MV)
Measurements
Measurements
NetworkStatus/
performance
Aggregated set point
Individual setpoints
TechnicalAggregation (MV)
AggregatedFlexibility (MV)
Measurements
WAN NetworkProvider(s)
Markets
Price signal
Aggregated setpoint (MV)
NetworkStatus/
performance
Individual setpoints
Aggregated flexibility (LV)
Individual setpoints (MV)
Measurements
Aggregated flexibility (MV)
Weather information
Bids
Accepted bids
Setpoints
Measurements
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
QoS/Network/reconfiguration
QoS/Network/reconfiguration
AN congestion detection and reaction
AN congestion detection and reaction
QoS/Network/reconfiguration
QoS/Network/reconfiguration
Aceessreconfiguration
Aceessreconfiguration
WAN congestion detection and reaction
WAN congestion detection and reaction
Aceessreconfiguration
Aceess reconfiguration
Aceess reconfiguration
Lost network connectivity
This scenario addresses the case where devices loose connectivity at the network layer. The case assumes a certain notion of connectivity, e.g. as in TCP.
Scenario
Scenario Name : Lost Network Connectivity
Step
No.
Event Name of
Process/Activit
Description
of
Service Information
Producer
Information
Receiver
Information
Exchanged
Technical
Requiremen
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y Process/Act
ivity
(Actor) (Actor) ts R-ID
1 Network
connection
is lost
Network manager A timeout or
other type of
error triggers
a detection of
a lost
network
connection.
Assumes a
notion of a
logic
connection
between
entities.
GET Network
provider
Information
access manager
Error signal
2 Reestablishm
ent of
connection;
potentially try
different
network
interfaces in
this process.
EXECUTE Information
access
manager
Target device Connection
signals
TSOAN NetworkProvider(s)
MV grid controlRetailer
Forecast ProviderTechnical
Aggregation (LV)
LV grid control
Individual setpoints (MV)
Large DERMicro DER/
Intermediate DER/Prosumer
Consumer
Measurements
Aggregated flexibility (LV)
Aggregated set point
AggregatedFlexibility (LV)
DMS
Weather information
Setpoint
Aggregated flexibility (MV)
Aggregated Setpoint (MV)
MeasurementsMeasurements
NetworkStatus/
performance
Aggregated set point
Individual setpoints
TechnicalAggregation (MV)
AggregatedFlexibility (MV)
Measurements
WAN NetworkProvider(s)
Markets
Price signal
Aggregated setpoint (MV)
NetworkStatus/
performance
Individual setpoints
Aggregated flexibility (LV)
Individual setpoints (MV)
Measurements
Aggregated flexibility (MV)
Weather information
Bids
Accepted bids
Setpoints
Measurements
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
NetworkStatus/
performance
AN Lost network connection
Timeoutmessage
Timeoutmessage
Success OK
NetworkStatus/
performance
NetworkStatus/
performance
AN Lost network connection
Timeoutmessage
Timeoutmessage
Success OK
Reconnect&pot. net. Reconf.
Reconnect&pot. net. Reconf.
Re-establishment of access
Re-establishment of access
10.3.5 Information Exchanged
Information Exchanged
Name of Information Description of Information Exchanged Requirements to information data R-ID
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Exchanged
Measurements Set of measurements from assets to upper level
control.
Individual setpoints Setpoints for assets in MV/LV grids such as
active and reactive power references, voltage
references, etc.
Network Status/Performance
Registration information; entity
capability
Deregistration information; who is
deregistering
IP address of information source; capability;
Network location information,
interface specification
IP address; interface possibilities;
Request for information or
subscription request for information
Request information for information
subscription; requirements to information
quality, delivery times etc.
10.3.6 Common Terms and Definitions
Common Terms and Definitions
Term Definition
Entity An entity is defined as some functional component (SW and HW) that will need to interact with the
smartc2net platform
Platform The communication platform that provides services and functionality for the control algorithms to
efficiently and reliably access distributed information elements
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10.4 USE CASE NAME: Automated Meter Reading (AMR) and Customer Energy
Management Systems (CEMS)
10.4.1 Description of the Use Case
10.4.1.1 Name of Use Case
Use Case Identification
ID Domain(s)
Name of Use Case
Distribution Grid,
Customer
Automated Meter Reading (AMR) and Customer Energy Management
Systems (CEMS)
10.4.1.2 Version Management
Version Management
Changes /
Version
Date Name
Author(s) or Committee
Domain
Expert
Area of
Expertise /
Domain /
Role
Title Approval
Status draft, for comments,
for voting, final
0.01 11.01.2013 CH/TUDO Draft
0.02 27.01.2013 FTW Draft
0.05 28.01.2013 CH/TUDO Draft for
comments
0.06 10.03.2013 CH/TUDO
0.08 21.03.2013 TUDO
0.09 25.03.2013 TUDO Draft
0.10 15.05.2013 Antonio Bovenzi (RT) Threat
Analysis
Researcher Draft
0.12 17.05.2013 FK/TUDO Draft
0.15 07.06.2013 FK/TUDO Draft
10.4.1.3 Scope and Objectives of Use Case
Scope and Objectives od Use Case
Related business case -
Scope Power Grid domains:
- Distribution networks - Households
ICT domains:
- Home Area Networks - Neighbourhood Area Networks
Objective
Automated Meter Reading:
Collection of energy consumption data from electric, gas, water and heating metering devices
Transmission of aggregated data from the households to the energy utilities/meter reading operators for billing and accounting
Provide (local) feedback system to the customers in order to provide transparent insight on the current energy consumption and enabling indirect demand side management
Aggregate information of energy consumption in order to balance the
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distribution grid by enabling direct demand side management
Customer Energy Management Systems:
Improve distribution grid stability by enabling direct demand side management
Reduce energy costs for consumers by shifting flexible loads to less expensive time slots or improve utilization of local energy resources
Provide added-value services to the customers
10.4.1.4 Narrative of Use Case
Narrative of Use Case
Short description – max 3 sentences
Automated Meter Reading (AMR) is an enabling technology, which is capable of generating precise
multi-sector metering data and aggregate them on local grid operator side for large-area and in-
house analysis of current energy consumptions as well as grid load conditions. Additionally, current
efforts in context of the Internet of Things aim to connect more devices in the household to create a
more intelligent Home Area Network (HAN) including components of Customer Energy Management
Systems (CEMS) like Distributed Energy Resources (DER) and storages, demand side management,
domestic electric vehicle charging and user interaction. In context of AMR, this adds an additional
way of home building automation by combining the energy consumption of accordant components
with the current status of the energy grid to improve its stability by shifting flexible loads balanced
with the neighborhood area network.
Complete description
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AMR is often referred to as the key application for enabling a Smart Grid. Basically, AMR represent
different approaches for automatically collecting energy consumption data from electric, gas, water
and heating metering devices and transmitting these data to the meter reading operator for billing
and accounting. This information enables the energy utilities for an accurate meter reading and a
detailed forecast of the predicted energy consumption. Since several years AMR systems are already
deployed mainly for industrial and commercial customers, based upon an integrative approach by
combing the actual metering components and a WAN interface for remote meter reading. Due to the
European Mandate M/441, a monthly billing for the customer and a roll-out of Smart Meter in 80%
of all European households until 2020 is targeted, which requires cost-efficient, modular concepts for
the comprehensive deployment of Smart Metering devices in a large number of households
considering a variety of application scenarios. Due to different technology life cycles for energy
components and ICT components a modular system is targeted in most of the approaches. Usually a
Metering HAN Gateways collect and store metering data from several metering devices, like
electricity, gas, water and heating meters by short range radio, e.g. ZigBee or Wireless M-Bus. The
collected data is securely transmitted bundled to the meter reading operator by different access
technologies, based on wireless, wired or PLC technologies. Moreover, a local feedback system gives
the consumer/prosumer transparent insight into his current energy consumption. In conjunction
with available tariff information motivation for reducing overall power consumption can be achieved.
The high-level AMR system architecture is depicted in Figure 91 consisting of the following
components:
1) Electricity metering devices collecting electrical energy consumption in short term intervals enabling variable time intervals and different tariff options.
2) Sub-Metering devices for gas, water, heating collecting energy consumption in long term intervals in order to provide automated meter reading
3) A communication gateway (HAN metering gateway) collects data from the metering and sub-metering devices via short range transmission technologies and aggregates data for providing wide area connectivity to the meter reading operator/energy utility.
4) A user feedback system, which can consist of a display or a PC application, provides feedback on a short term interval to the customers in order to enable indirect DSM by providing current pricing and consumption information.
5) A meter reading operator is providing the infrastructure for the metering devices and is located on the backend system side.
In the context of SmartC2Net, the following AMR scenarios with reference to [4-9] have been
identified. A detailed scenario structure with appropriate use cases is illustrated in Figure 93. It is
depicted how the individual physical components are laid out. The Smart Meters (SM) of the AMR
use case measure the amount of energy, gas and water used in the household. Therefore a
connection between the flexible and non-flexible loads and the Smart Meter is necessary. The SM
interfaces with the Local Network Access Point (LNAP) which provides the WAN connection for
upload of the metering data. It is to be considered that, due to legal restrictions out of privacy
concerns, it is possible that a direct connection between SM and Energy Management Gateway
(EMG) might not exist. A EMG has the ability to controls flexible loads, private parking spots and
home automation devices. The state of these devices, along with current tariff and consumption
information, is made available for the consumer by an external display which also provides a certain
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degree of control over the CEMS. The LNAP has an interface to the Neighborhood Network Access
Point (NNAP) which itself connects to the Head End System (HES) with its subsequent set of devices
and roles. These are the Meter Data Management System (MDMS), Metering Data Aggregator
(MDA), Distribution Network Operator (DSO), Aggregator, Metering Operator and Energy Service
Provider.
Scenario 1: Measurement (MM)
For considering all amount of customer’s supply, meter reading and tariff configuration are
integrated in the measurement procedure. Different actors (A, B, C – see chapter 10.4.3.1)
participate in the measurement procedure to ensure that tariff parameters are kept valid (Set tariff
parameters) on provider- and customer side. Meter reading can be divided in two sub-procedures,
Reading on demand and Scheduled reading:
MM.01 Reading on demand See Figure 94 and Figure 95
This use case describes how a request may be made to the AMI (Advanced Monitoring
Infrastructure) for an on demand reading and how the AMI responds. The request may relate
to current register / index readings or to historical values (e.g. stored at the end of a billing
period). The request may be issued by Actor A or Actor B. This use case may be used to
retrieve not only the values of billing registers / indexes but any values that need to be read
on demand, under the conditions that it is for authenticated authorized actors and with full
respect of data privacy.
MM.02 Scheduled reading See Figure 97, Figure 98 and Figure 99
This use case describes how Actor A obtains meter readings at regular intervals and how a
meter reading schedule (which indicates what data has to be read from the smart meter at
which point in time) is configured.
MM.03 Set tariff parameters See Figure 100, Figure 101 and Figure 102
For billing configuration, the setup of billing parameters is needed. The use case Set billing
parameters describes Actor A setting the parameters that represents consumer account
arrangements. Billing parameters are Payment mode, Tariff scheme, Prices, Thresholds and
response actions and Data sets.
Scenario 2: Customer information provision (CI)
CI.01 Provide information to consumer See Figure 103, Figure 104, Figure 105 and Figure 106
This use case describes how information may be provided to consumers by the AMI system
via the simple external consumer display.
Information may be generated by actors outside the AMI system and communicated via the
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AMI infrastructure or may be generated within the system and presented for display on
devices within the metering system.
Scenario 3: Collect AMI events and status information (ES)
The AMI provides functionality to screen and manage AMR related information with focus on supply
quality as well as tamper and fraud detection.
ES.01 Tamper and fraud detection Detect tampering of the metering system (physical integrity, electromagnetic field,
communication, security, fraudulent use of the meter by customer, etc.) and detect tamper
of connection to network.
ES.02 Manage supply quality See Figure 107, Figure 108 and Figure 109
This primary use case describes how information concerning supply quality is being
monitored by providing it on a regular basis to actor A and/or sending it on a regular basis to
a simple external consumer display.
ES.03 Advanced monitoring Uploading of data and information to permit e.g. monitoring of outages (electricity), network
leakage detection (water) and identification of possible meter malfunction.
In addition, diagnostics (mainly for electronic components), the meter / metering system,
status information (e.g. battery condition credit/prepayment mode) and identification of
incorrectly sized or blocked meters(water) can be performed.
Additionally to the basic functionality of the AMR deployment, a more balanced usage of volatile
renewable energy sources (RES) and shift-able and controllable load system (CLS) in the distribution
grids is possible by an actively integration of the components on the customers side. In this context,
several customer energy management system (CEMS) are presented, like locally managed and self-
sustaining Micro Grids, virtual power plant and centralized load coordination like DSM or DER based
on dynamic energy prices. All approaches focus on the bidirectional integration of DER and
prosumers (producers and consumers) from both power and communication engineering's point of
view. This includes volatile RES such as wind farms and photovoltaic systems, as well as energy-aware
households, which are enabled by AMR to get a detailed forecast of the energy demand and
additional transparency in energy consumption at the customer's side. Moreover, based on CLS and
Distributed Generation (DG) through combined heat and Power (CHP) generation, micro-turbines
and intelligent photovoltaic (PV) panels, the ability to balance load peaks and valleys is given. These
approaches require, however because of the distributed installations and small shift-able load
potential, an aggregation of multiple DER, which creates a common control, for example by means of
incentive systems and a sufficient amount of potential shift provides. Through concepts such as VPP,
microgrids and energy hubs, different components are combined using various networking concepts
into a logical, partly independent group (e.g. isolated networks). At this point, the seamless
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integration and reliable and near real-time connectivity within the households by a CEMS, which is
required for DER and DSM at the customers side, are key capabilities of reliable power distribution
grids.
The high-level CEMS system architecture is depicted in Figure Figure 91 consisting of the following
components:
6) Flexible and non-flexible load systems within the households (e.g. air conditioning units, household appliance, etc.)
7) Decentralized power production / distributed energy resources (e.g. photovoltaic panels, local CHP, micro wind turbines, etc.)
8) A communication gateway (control hub) providing connectivity to the in-house networks and components and enabling remote access and data services to the WAN.
9) Electricity metering devices collecting electrical energy consumption in short term intervals enabling variable time intervals and different tariff options.
10) An enhanced user feedback system, which provides the basic metering functionality and additional services for indirect and direct DSM, e.g. the customers provide flexibilities by enabling a flexible start time for their household appliances, like washing machines or dish washers.
11) In order to aggregate a large number of customers, an external service provider collects and manages the flexibilities, which are provided by the customers. This service can be covered by energy utilities or external service providers.
All in-house components assume to be connected via a CEMS, which can be realized by a dedicated
wired or wireless home automation system (e.g. narrowband PLC, broadband PLC, BUS systems,
ZigBee, W-MBus, etc.) or a shared medium provided by the customers in-house networks (e.g.
wireless LAN, broadband PLC, etc.). At least one access technology (at least cellular networks), but
possible more communication means depending on the existing possibilities, e.g. power line, 3G or
fiber (if already installed in the household) and communication technologies as well as operators
may differ between households.
In the communication infrastructure some entities exists that performs the important role of a) data
aggregation from the various sources of large numbers of households and other buildings/sites that
extracts features usable by the prediction and control algorithms applied, b) power prediction based
on the aggregated information, as well as other information such as weather forecasts and finally c)
the control of the energy grid based on the predicted power need. All of this operates, as mentioned
in local environment and will need to be coordinated with the MV grid whereas communication on
the various levels also needs to happen here.
The control network is shown in Figure 91 and consist of the following domains:
12) Connected to the control hub within households via the communication hub 13) Connected to data aggregation, power prediction and control units within the low voltage
grid
In the context of SmartC2Net, the following CEMS scenarios with reference to [9-16] have been
identified. A detailed scenario structure with appropriate use cases is illustrated in Figure 93. It is to
be considered that, due to legal restrictions out of privacy concerns, it is possible that a direct
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connection between SM and EMG might not exist.
Scenario 1: Demand and generation flexibility for technical and commercial operations
This scenario is providing use cases on flexibility features as DER, active customers/active load and
flexibility use for markets, services or grid operation. The use cases direct load and generation
management, flexibility offerings as well as receiving consumption, price or environmental
information for further action by consumer or a local energy management system are contained in
this scenario.
Direct load and generation management See Figure 110 and Figure 111
Signals and metrological information are provided to the home/building via an interface
called the Smart Grid Connection Point (SGCP). The following signals can be distinguished:
1. Direct - load / generation / storage management 2. Emergencies
The functions described below can be labelled as a “Direct load control” use case, following
the definition of Eurelectric, which is referenced in the Sustainable Processes workgroup’s
report.
Flexibility offerings Not included within this use case
Flexibility offerings are sent from flexibility providers to one or more (potential) users of
flexibility. These offerings are negotiated and if successful exercised by the acquiring party.
The offerings state the available flexibility in the dimensions of time, power/energy and
finance.
Receiving consumption, price or environmental information for further action by consumer or a local energy management system See Figure 112, Figure 113, Figure 114 and Figure 115
This use case describes how information regarding price and environmental aspects is sent
from upstream actors to CEMS and how information regarding energy consumption or
generation as well as smart device statuses are being sent back to the consumer and
upstream actors.
Scenario 2: Grid related use cases
Several use cases are describing existing functionalities, especially coming from power automation,
network operation and monitoring (SCADA). Those use cases are well known today, but have to be
adapted to the Smart Grid in order to realize spreading of intermittent power sources (generation or
storage) at any level of voltage.
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Grid related use cases in smartC2net are divided in sub use cases Voltage control and power flow
optimization VVO, Microgrid management, Monitoring the distribution grid, Fault Location,
Isolation and Restoration (FLIR) as well as Forecast. This use cases are driven by grid management
and control algorithms and are detailed in [18].
Scenario 3: Electric vehicle charging and low voltage grids
Charging of electrical vehicles in low voltage grids is challenging due to highly synchronized demand
patterns of charging as well as high loads. This use case covers the controlled charging of electrical
vehicles in a low voltage grid, taking into consideration the EV owner, a charging infrastructure
owner/provider as well as the DSO. Regarding the latter, the use case aims to utilize the high demand
flexibility of the charging process to balance grid and energy in the low voltage grid [19].
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10.4.1.5 General Remarks
General Remarks
-
10.4.2 Diagrams of Use Case
Diagram of Use Case
Figure 91: Advanced Smart Meter Reading and Customer Energy Management System Scenario
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Simple external
consumer display
Home automation end device
Energy Management Gateway (EMG)
Smart Meter (SM)
Customer Energy Management System (CEMS)
Substation Level Operator LevelAutomated Meter Reading (AMR)
Local Network Access Point
(LNAP)
Flexible Loads
Non-Flexible Loads
Metering Operator
Private Charging Spot
Aggregator
Distribution Network Operator
Energy Service Provider
Metering Data Aggregator
Related to EV Use Case
Related to External GenerationUse Case
Related to External GenerationUse Case
Meter Data Management System
Head End System (HES)
Neighborhood Network Access Point (NNAP)
Figure 92: Physical components of the use case and their locations in the Smart Grid setup
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DG.01. Direct Load /Generation
management
DG.02. HL-UC Flexibility offerings
DG.03. HL-UC Receiving consumption, price or environmental information for further action by consumer or a local
energy management system
CI.01. Provide Information to
consumer
ES.01. Tamper and Fraud detection
ES.02. Manage supply quality
ES.03. Monitoring
MM.01. Obtain meter reading on demand
MM.02. Obtain scheduled meter
reading
MM.03. Set tariff parameters
Keys
Customerinformation provision AMR Use Cases
<< extends >>
Actor A Actor B Actor C
Demand and Generationflexibility for technical and
commercial operations
Electric Vehicle REF: Use Case Name: Electrical Vehicle
Charging in Low Voltage Grids
Reference to use casedocument
Use Case ClusterUse Case Cluster
Use Case
Actor D
[WGSP Actor B]
[WGSP Actor A]
Collect AMI eventsand status information
<< extends >>
Measurement
Grid related REF: Use Case Name:
External Generation Site and Island Mode
CEMS Use Cases
Figure 93: Detailed use case clustering structure
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Diagrams of AMR Use Case
The diagrams of AMR use case are structured in sub-processes billing, customer information
provision as well as collect AMI events and status information.
Diagrams of sub-process Measurement (MM)
Diagram of Use Case
MM.01. Obtain meterreading on demand
SU3. Read meter
Actor BActor A
<<includes>>
Figure 94: MM.01 Obtain meter reading on demand (refer to [4])
Actor A EMG Smart Meter
1: Send (Meter read request)
2: Invoke SU3()
3: SU3 invoked()
4: Send (Requested reading)
Figure 95: Sequence diagram MM.01.01 - Obtain remote meter reading on demand (refer to [4])
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Actor A Smart Meter
1: Send(Meter read request)
2: Send (Meter read)
Figure 96: Sequence diagram MM.01.02 - Obtain walk-by meter reading on demand (refer to [4])
ActorA
MM.02. Obtainscheduled meter reading
SU3. Read Meter
MM.02.01. Configurereading schedule
SU1. Writeinformation
<<extends>>
<<includes>>
<<includes>>
Figure 97: MM.02 Obtain scheduled meter reading (refer to [5])
Actor A EMG Smart meter
1: SU3 invoked()
2: Send (Meter read)()
Figure 98: Sequence diagram MM.02.01 - Obtain scheduled meter reading (refer to [5])
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Actor A EMG Smart Meter
1: Send (Reading schedule)
2: Invoke SU1()
3: SU1 invoked()()
4: Send (Confirmation)
sd optional
Figure 99: Sequence diagram MM.02.02 - Configure reading schedule (refer to [5])
MM.03. Set billingparameters
SU1. Writeinformation
Actor BActor A
<<includes>>
Figure 100: MM.03 Set tariff parameters (refer to [6])
Actor A EMG Smart meter Display
1: Send (Billing parameter)
2: Invoke SU1()
3: Send(Notification)
4: SU1 invoked()
5: Send(information)
sd optional
sd optional
Figure 101: Sequence diagram MM.03.01 - Set tariff parameter in the smart meter (refer to [6])
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Actor A EMG NNAP / LNAP
1: Send(Billing parameter)
2: Invoke SU1
3: SU1 invoked
4: Send(confirmation)
sd optional
Figure 102: Sequence diagram MM.03.02 - Set tariff parameter in the LNAP/NNAP(refer to [6])
Diagrams of sub-process customer information provision
Diagram of Use Case
CI.01. Provideinformation to customer
SU1. Writeinformation
Actor A
Actor C
Actor B
Figure 103: CI.01. customer information provision (refer to [8])
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Actor A EMG Smart meter
1: Send(information message)
2: Invoke SU1()
3: SU1 invoked()
4: Send(confirmation)
sd optional
Figure 104: Sequence diagram CI.01.01 - Send information to meter display (refer to [8])
Actor A EMG Smart meter
1: Send(information message)
2: Invoke SU1()
4: SU1 invoked()
5: Send(confirmation)
sd optional
Smart meter
3: Send(Information message)
Figure 105: Sequence diagram CI.01.02 - Send information to simple external consumer display (refer to [8])
Smart meter Display
1: Send(Actual meter reads / power quality and/or device status)
Figure 106: Sequence diagram CI.01.03 -– Smart Meter publishes information on simple external consumer
display (refer to [8])
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Diagrams of sub-process collect AMI events and status information
Diagram of Use Case
ES.02.01 Configure powerquality parameters to be
monitored
MM.01 Obtain meterreading on demand
MM.02 Obtainscheduled meter reading
CI.01.01 Send toinformation to meter display
ES.02 Managesupply quality
SU1. Writeinformation
SU3. Read meter
Actor A Actor C
<<extends>><<extends>> <<extends>> <<extends>>
Figure 107: ES.02 - Manage supply quality (refer to [7])
Actor A EMG Smart Meter
1: Send(Power quality parameters)()
2: Invoke SU1()
3: SU1 invoked()
4: Send (Confirmation)
sd optional
Figure 108: Sequence diagram ES.02.01 - Configure power quality parameters to be monitored (ref. [7])
Smart Meter Display
1: Send (Supply quality message)
Figure 109: Sequence diagram ES.02.02 - Smart meter sends information on power quality to display (refer to
[7])
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Diagrams of CEMS Use Case The diagrams of CEMS Use case are structured in sub-processes grid related use cases as well as
demand and generation flexibility for technical and commercial operations.
Diagrams of sub-process demand and generation flexibility for technical and commercial
operations (DG)
Diagram of Use Case
Actor A MDM EMG NNAPSmart Metering Gateway
(LNAP) Actor D Energy Management Gateway CEMS Smart Appliance / Generators Display
Load Mgmt. Command
Load Mgmt. command
Load management system
CCM
Start of load adjustment notification
Order of load adjustmend
Feedback status
End of load adjustment notification
End of load adjustment
End of load adjustment period + sending load curve recorded for this period
Feedback status
End of load adjustment period + sending load curve recorded for this period
par
par
Announcement of load adjustment
Expected change in consumption
Expected change in consumption
Figure 110: DG.01.01 - Direct load / generation demand – appliance has end-decision about its load
adjustment (refer to [14])
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Actor A MDM EMG NNAPSmart Metering Gateway
(LNAP)Actor D Energy Management Gateway CEMS Smart Appliance / Generators Display
Load Mgmt. Command
Load Mgmt. command
CCM
Load adjustment notification
Start of load adjustmend period
Feedback status
End of load adjustment notification
End of load adjustment period
Confirmation that load has been adjusted
Feedback status
Confirmation that load has been adjusted
par
par
Figure 111: DG.01.02 - Direct load / generation demand - appliance has no control over its own load
adjustment (refer to [14])
Actor A MDM EMG NNAPSmart Metering Gateway
(LNAP)Actor D Energy Management Gateway CEMS Smart Appliance / Generators Display
Individual appliance consumption / generation information
Total and / or forecased house consumption / generation
Total and / or forcased house consumption / generation
Total and/or forecased house consumption / generation
Total and/or forecased house consumption/generation
par
Total and/or forecased house consumption/generation
Total and/or forecased house consumption/generation
Total and/or forecased house consumption/generation
Total and/or forecased house consumption/generation
Figure 112: Sequence diagram DG.03.01 - Information regarding power consumption / generation of
individual appliances (refer to [16])
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Actor A MDM EMG NNAP Smart Metering Gateway(LNAP)
Actor D Energy Management Gateway CEMS Smart Appliance/Generators Display
Total and / or forecased house consumption / generation
Total and / or forcased house consumption / generation
Total and/or forecased house consumption / generation
Total and/or forecased house consumption/generation
par
Total and/or forecased house consumption/generation
Total and/or forecased house consumption/generation
Total and/or forecased house consumption/generation
Total and/or forecased house consumption/generation
Smart Meter Functionality
Total house consumption
Total house consumption
Figure 113: Sequence diagram DG.03.02 - Information regarding total power consumption (refer to [16])
Actor A MDM EMG NNAPSmart Metering Gateway
(LNAP) Actor D Energy Management Gateway CEMS Smart Appliance/Generators Display
Gateway
Price and environmental information
Price and environmental information
par
Confirmation
Price and environmental information
Price and environmental information
Price and environmental information
Price and environmental information
Price and environmental information
par
Confirmation
Confirmation New price and environmental information
New price and environmental information
Confirmation reception new price and environmental information
Figure 114: Sequence diagram DG.03.03 - Price & environmental information (refer to [16])
CEMS Smart Appliance/Generators Display
Information on total consumption & subscribed power
Warning signal
Warning signal
Figure 115: Sequence diagram DG.03.04 - Warning signals based individual appliances consumption (refer to
[16])
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10.4.3 Technical Details
10.4.3.1 Actors: People, Systems, Applications, Databases, the Power System, and Other
Stakeholders
Figures
Actor AMetered Data Aggregator
Meter Data Collector
Meter Operator
Meter Data Management
Actor B
Consumer
Actor CActor D
Supplier
Energy Service Provider
Head End System (HES)
Metering End Device External Consumer Display Home Automation End Device
Figure 116: External Actors (refer to [1])
Actors
Grouping (Community) Group Description
Actor Name see Actor List
Actor Type see Actor List
Actor Description see Actor List
Further information
specific to this Use Case
EXTERNAL ACTORS
A Summarized Actors (
Figure 116, refer to [1])
External actor interacting with the system
functions and components via the HES
MDA (belongs to Actor A) System Metering Data Aggregator
Entity which offers services to aggregate
metering data by grid supply point on a
contractual basis.
NOTE: The contract is with a supplier. The
aggregate is of all a supplier's consumers
connected to a particular grid supply point.
The aggregate may include both metering
data and data estimated by reference to
standard load profiles
MDMS / MDM (belongs to
Actor A)
System Meter Data Management System
System for validating, storing, processing
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and analysing large quantities of meter
data.
B Summarized Actors (
Figure 116, refer to [1])
External actor interacting directly with the
smart meter (Metering End Device).
Consumer (belongs to Actor
B)
- End user of electricity, gas, water or heat.
NOTE: As the consumer can also generate
energy using a Distributed Energy Resource,
he is sometimes called the "Prosumer".
MO (belongs to Actor B) People/Company Meter Operator
Entity which offers services on a contractual
basis to provide, install, maintain, test,
certify and decommission physical metering
equipment related to a supply.
C Summarized Role (
Figure 116, refer to [1])
External actor interacting directly with the
simple external consumer display.
Consumer (belongs to Actor
C)
Role Consumer/Prosumer
D Summarized Role (
Figure 116, refer to [1])
External actor interacting directly with the
home automation end device.
Consumer (belongs to Actor
D)
- Consumer/Prosumer
ESP (belongs to Actor D) People/Company Energy Service Provider: Organization
offering energy services to the consumer.
NOTE: an example consists of a role
responsible for creating awareness
regarding rational energy consumption.
They also provide the required knowledge
to the consumer allowing him to reduce his
energy consumption. Within this role he will
supply data / information to the consumer
through the meter.
Supplier People/Company Entity that offers contracts for supply of
energy to a consumer (the supply contract).
Within this role he will initiate DSM
activities
NOTE: In some countries referred to as
Retailer
E Summarized Role (refer
to [1])
External actor responsible for the
installation, operation, maintenance and
de-installation of the system components. It
may access, if properly identified and
authorized, those components either
directly, via local operation and
maintenance interfaces, or from a system
component from a higher hierarchical level
(e.g. meters may be accessed for
maintenance purposes via NNAPs or the
HES).
MO (belongs to Actor E) People/Company Meter Operator
Entity, which offers services on a
contractual basis to provide, install,
maintain, test, certify and decommission
physical metering equipment related to a
supply.
DNO (belongs to E) People/Company Distribution Network Operator
Market surveyor (belongs to
Actor E)
People/Company Actor responsible for evaluating the
conformity of the Metering End Device to
the requirements of Directive (2004/22/EC).
Smart appliance / Generator
(external actor)
System The smart appliance with integrated EM,
directly receiving data from the grid,
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through the SGCP. The appliance may
contain of be connected to a Plug in
electricity meters that measures individual
appliance consumption or output.
Since the smart appliance / generator is
outside the scope of the SGCG, it must be
seen as an external actor
INTERNAL ACTORS (refer to [1])
Head End System (HES) System Central Data System collecting data via the
AMI of various meters in its service area. It
communicates via a WAN directly to the
meters and/or to the NNAP or LNAP.
NNAP System The Neighbourhood Network Access Point
is a functional entity that provides access to
one or more LNAP’s, metering end devices,
displays and home automation end devices
connected to the neighbourhood network
(NN). It may allow data exchange between
different functional entities connected to
the same NN.
LNAP System The Local Network Access Point is a
functional entity that provides access to
one or more metering end devices, displays
and home automation end devices
connected to the local network (LN). It may
allow data exchange between different
functional entities connected to the same
LN.
Smart Meter (SM) System Meter with additional functionalities one of
which is data communication.
Simple external consumer
display
System Display providing accurate information on
consumption, tariffs and so on in order to
increase consumer awareness.
Home automation end
device
System Device providing additional functionalities
enabling consumers to interact with their
own environment.
CEMS (Customer Energy
Management System)
System CEMS is any device/software or group of
them installed in the customer facilities
which allows the visualization of
metrological information, price and warning
signals by the customer and has the
capability to take action automatically or
after approval by customer on any home
appliances.
Energy Management
Gateway
System Equipment sending and receiving smart grid
related information and commands
between actor A and the CEMS, letting the
CEMS decide how to process the events.
The communication is often achieved
through an internet connection of through
a wireless connection
10.4.3.2 Preconditions, Assumptions, Post condition, Events
Use Case Conditions
Actor/System/Information/Contract Triggering Event Pre-conditions Assumption
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Access ICT Networks
No triggering event Households are
equipped with
control and
communication hubs
Primary network is cellular networks
Households No triggering event Houses are equipped
with smart meters
As a minimum the household power
consumption/production is measured
10.4.3.3 References /Issues
References
No. References Type Reference Status Impact on
Use Case
Originator/Organization Link
1 Report Smart Meters Co-
ordination Group -
Smart Metering Use
Cases
final All AMR use
cases
Smart Meters
Coordination Group
-
2 Report CEN-CENELEC-ETSI
Smart Grid
Coordination Group
– Sustainable
Processes
final ES.01, ES.03 CEN-CENELEC-ETSI Smart
Grid Coordination Group
-
3 CEN/CLC/ETSI/TR
50572:2011 E
Functional reference
architecture for
communications in
smart metering
systems
final All CEMS use
cases
CEN/CLC/ETSI/ -
4 Report BI.01. Obtain meter
reading on demand
draft MM.01 CEN/CLC/ETSI/ -
5 Report BI.02. Obtain
scheduled meter
reading
draft MM.02 CEN/CLC/ETSI/ -
6 Report BI.03. Set billing
parameters
draft MM.03 CEN/CLC/ETSI/ -
7 Report MSQ.01. Manage
supply quality
draft ES.02 CEN/CLC/ETSI/ -
8 Report CI.01. Provide
information to
consumer
draft CI.01 CEN/CLC/ETSI -
9 Report WGSP-0301 Short
term load and
generation
forecasting
draft GR.01 CEN/CLC/ETSI/ SM-CG
Use case
repository
10 Report WGSP-0200 Voltage
control and power
flows optimization
VVO
draft GR.02 CEN/CLC/ETSI/ SM-CG
Use case
repository
11 Report WGSP-0400
Microgrid
management
draft GR.03 CEN/CLC/ETSI/ SM-CG
Use case
repository
12 Report WGSP-0600
Monitoring the
distribution grid
draft GR.04 CEN/CLC/ETSI/ SM-CG
Use case
repository
13 Report WGSP-0901
Congestion
management by
direct control
draft GR.05 CEN/CLC/ETSI/ SM-CG
Use case
repository
14 Report GENERIC USE CASE
WGSP-2120
Managing energy
draft DG.01 CEN/CLC/ETSI/ Link
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consumption or
generation with
smart appliances
15 Report WGSP-2128 - High
level use case -
Flexibility offerings
draft DG.02 CEN/CLC/ETSI/ SM-CQ
Use case
repository
16 Report GENERIC USE CASE
WGSP-2110
Receiving
metrological, price
or environmental
information for
further action by
consumer or a local
energy management
system
draft DG.03 CEN/CLC/ETSI/ Link
17 EU mandate M/441
18 SmartC2Net Use case
description
Sub-use Case 2.3:
External Generation
Site
draft SmartC2Net consortium -
19 SmartC2Net Use case
description
USE CASE NAME:
Electrical Vehicle
Charging in
Low Voltage Grids
draft SmartC2Net consortium -
20 Research Paper Basic concepts and
taxonomy of
dependable and
secure computing
Published - Avizienis, A. ; Vytautas
Magnus Univ., Kaunas,
Lithuania ; Laprie, J.-C. ;
Randell, B. ; Landwehr, C.
Link
10.4.3.4 Further Information to the Use Case for Classification / Mapping
Classification Information
Relation to Other Use Cases Electric vehicle charging within the households is covered by the EV UC and information exchange is required. Interfaces to the control
algorithms of the MW UC needs to be specified.
Level of Depth
HL-UC
Prioritization
Mandatory
Generic, Regional or National Relation
Smart metering has a generic relation to all European countries due to the mandate M/441 of the EU to get 80% smart metering
deployments until 2020. The control aspect needs to be aligned to the European mandate M/490, but depends on the actual regional and
national deployed system architecture and needs to be evaluated for all different scenarios.
View
Technical
Further Keywords for Classification
10.4.4 Step by Step Analysis of Use Case
Scenario Conditions
No. Scenario
Name
Primary Actor Triggering Event Pre-Condition Post-Condition
Scenario AMR
Measurement (MM), (refer to [4-6])
PS1 MM.01.01 -
Obtain
remote
Actor A
Actor A decides he wants a
particular meter read or
meter reads.
The metering and
communications are
installed, operating.
Success
Actor A has the read he requested.
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Scenario Conditions
No. Scenario
Name
Primary Actor Triggering Event Pre-Condition Post-Condition
meter
reading on
demand
Minimal Guarantee
The metering system is operating as
before the request.
Actor A is aware of the reason for not
receiving the read.
PS2 MM.01.02
- Obtain
walk-by
meter
reading on
demand
Actor B
Actor B decides he wants a
particular meter read or
meter reads.
Success
Actor B has the read he requested.
Minimal Guarantee
The metering system is operating as
before the request.
Actor B is aware of a reason for not
receiving the read.
PS3 MM.02.01 -
Obtain
scheduled
meter
reading
Actor A The timer triggers a meter
reading.
There is a valid
contract between
actor A and
consumer.
Communication
with the meter is
established.
A reading schedule
and data collection
scheme (e.g. load
profile) are
established and
activated in the
system.
Success:
Actor A has received all required metering
data.
Minimal Guarantee:
Actor A has the reason explaining why he
did not receive the expected information
PS4 MM.02.02 -
Configure
reading
schedule
Actor A Actor A needs readings from
the meter on a regular basis
Communication
between all actors
can be established.
Success:
Reading schedule is established in the
system.
Optionally, reading schedule has been
activated.
Optionally, confirmation is received by
Actor A.
Minimal Guarantee
The metering system is operating as
before the request.
Actor A has the reason explaining why the
request was or will not be completed.
PS5 MM.03.01
– Set tariff
parameter
in the
smart
meter Actor A
Actor A wants to set a billing
parameter that is not yet
known by the Smart Meter.
Communication
between all actors
can be established.
Success
The billing parameter is received by the
Smart Meter.
Optionally, billing parameter has been
activated.
Optionally, the change of parameter is
shown on the display
Optionally, confirmation is received by
Actor A.
Minimal Guarantee:
Actor A has a reason explaining why the
request was or will not be completed
PS6 M.03.02 –
Set tariff
parameter
Actor A Actor A wants to set a billing
parameter that is not yet
known by the LNAP/NNAP.
Communication
between all actors
can be established.
Success
The billing parameter is received by the
LNAP/NNAP.
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Scenario Conditions
No. Scenario
Name
Primary Actor Triggering Event Pre-Condition Post-Condition
in the
LNAP/NNA
P
Optionally, billing parameter has been
activated.
Optionally, confirmation is received by
Actor A.
Minimal Guarantee:
Actor A has a reason explaining why the
request was or will not be completed
Customer information provision (CI), (refer to [8])
PS7 CI.01.01 -
Send
information
to meter
display
Actor A Actor A wants to show
information on the meter
display.
Communication
between all actors
can be established.
Success:
The information is received by the meter
display.
Optionally, actor A received confirmation.
Minimal Guarantee
The message is not displayed
PS8 CI.01.02 -
Send
information
to simple
external
consumer
display
Actor A Actor A wants to show
information on a simple
external consumer display.
Communication
between all actors
can be established.
Success:
The information is received by a simple
external consumer display.
Optionally, actor A received a
confirmation.
Minimal Guarantee
The message is not displayed
PS9 CI.01.03 -
Smart
Meter
publishes
information
on simple
external
consumer
display
Timer Timer triggers to smart
meter to display
information on actual meter
reads / power quality
and/or device status on the
simple external consumer
display
Smart meter has a
schedule indicating
at which times
which information
needs to be pushed
to the simple
external consumer
display
Communication
between all actors
can be established.
Success:
The information is received by a simple
external consumer display.
Minimal Guarantee
The message is not displayed
Collect AMI events and status information (ES) (refer to [7])
PS1
0
ES.02.01 –
Configure
power
quality
parameters
to be
monitored
Timer Actor A wants to configure
power quality parameters
to be monitored
Communication
between all actors
can be established.
There is a valid
contract between
Actor A and the
consumer.
Success:
Power quality parameters are received by
the Smart Meter.
Optionally, confirmation is received by
Actor A
Minimal Guarantee:
Actor A is aware of the reason for failure
PS1
1
ES.02.02 –
Smart
meter
sends
information
on power
quality to
display
Smart Meter Smart Meter is triggered to
display information about
supply quality
Information about
supply quality is
available in Smart
Meter.
Communication
between all actors
can be established.
Smart Meter has an
active schedule
Success:
Information is received by a display
Minimal Guarantee:
Information is not received by display
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Scenario Conditions
No. Scenario
Name
Primary Actor Triggering Event Pre-Condition Post-Condition
indicating when to
send messages to
the display.
Scenario CEMS
Demand and Generation flexibility for technical and commercial operations (DG) (refer to 14, 16]
PS1
2
DG.01 –
appliance
has end-
decision
about its
load
adjustment
Actor A or
Actor B
Actor A or Actor B wants to
send a load management
command to the market
Communication
connection between
all actors is
established
The consumer
configured the
CEMS and/or the
participating devices
(appliances and
generators). The
consumer
configured the
device settings and
thresholds
Information on total
consumption or
consumption per
appliance is
available in the
CEMS
The Smart Appliance / generator
executed the load management command
and Actor A or Actor B received the
feedback with a load curve recorded for
this period
PS1
3
DG.01.02 –
appliance
has no
control
over its
own load
adjustment
Actor A or
Actor B
Actor A or Actor B wants to
send a load management
command to the market
Communication
between all actors
can be established
The consumer
configured the
CEMS and/or the
participating devices
(appliances and
generators). The
consumer
configured the
device settings and
thresholds
Information on total
consumption or
consumption per
appliance is
available in the
CEMS
The appliance executed the load
management command and Actor A or
Actor B received the feedback
PS1
4
DG.03.01 –
Information
regarding
power
consumptio
n /
generation
of
Smart
appliance /
Generator
New consumption /
generation information is
available in the smart
appliance / generator
Communication
connection between
all actors is
established
(forecasted) consumption / generation is
received by actor A and/or actor B and/or
display
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Scenario Conditions
No. Scenario
Name
Primary Actor Triggering Event Pre-Condition Post-Condition
individual
appliances
PS1
5
DG.03.02 –
Information
regarding
total power
consumptio
n
Smart Meter New
consumption/generation
information is available in
the Smart Meter
Communication
connection between
all actors is
established
(forecasted) consumption/generation
information is received by actor A and/or
or Actor B and/or display
PS1
6
DG.03.03 –
Price &
environme
ntal
information
Actor A or
actor B
New price and
environmental information
is available in Actor A or
Actor B
Communication
connection between
all actors is
established
Price and environmental information is
received by Smart Appliances
PS1
7
DG.03.04 –
Warning
signals
based
individual
appliances
Smart
appliance
The CEMS received
information on a new
operation to be executed
The subscribed
power limits are
made known to the
smart appliance
Warning signal is received by display
and/or smart appliances
10.4.4.1 Steps – Normal
Scenario Name : Reference:
Scenario AMR
Measurement (MM)
MM.01.01 - Obtain remote meter reading on demand Ref. [4], subchapter 3.1.1
MM.01.02 - Obtain walk-by meter reading on demand Ref. [4], subchapter 3.2.1
MM.02.01 - Obtain scheduled meter reading Ref. [5], subchapter 3.2.1
MM.02.02 - Configure reading schedule Ref. [5], subchapter 3.1.1
MM.03.01 - Set tariff parameter in the smart meter Ref. [6], subchapter 3.1.1
MM.03.02 – Set tariff parameter in the LNAP/NNAP Ref. [6], subchapter 3.2.1
Customer information provision (CI)
CI.01.01 – Send information to meter display Ref. [8], subchapter 3.1.1
CI.01.02 - Send information to simple external consumer
display
Ref. [8], subchapter 3.2.1
CI.01.03 – Smart Meter publishes information on simple
external consumer display
Ref. [8], subchapter 3.3.1
Collect AMI events and status information (ES)
ES.02.01 – Configure power quality parameters to be
monitored
Ref. [7], subchapter 3.1.1
ES.02.02 – Smart meter sends information on power quality to
display
Ref. [7], subchapter 3.2.1
Scenario CEMS
Demand and Generation flexibility for technical and commercial operations (DG)
DG.01.01 – appliance has end-decision about its load
adjustment
Ref. [14], subchapter 2.1
DG.01.02 – appliance has no control over its own load
adjustment
Ref. [14], subchapter 2.2
DG.03.01 – Information regarding power consumption /
generation of individual appliances
Ref. [16], subchapter 2.1
DG.03.02 - Information regarding total power consumption Ref. [16], subchapter 2.2
DG.03.03 - Price & environmental information Ref. [16], subchapter 2.3
DG.03.04 - Warning signals based individual appliances Ref. [16], subchapter 2.4
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10.4.4.2 Steps – Alternative, Error Management, and/or Maintenance/Backup Scenario
Fault/threat analysis/scenarios
In this section the possible failures in the CEMS/AMR UC are considered. In particular, the focus is on
security threats that can hamper the CEMS main functionalities. Indeed, the CEMS may operate in a
very hostile environment since it can be connected to home automation devices and to the EMG by
means of shared network (e.g., the home WiFi, office LAN). The use of already deployed IP network is
extremely appealing since the cost for cabling and network interfaces is rapidly. However, IP-based
networks, when not well secured are subject to cyber security attacks.
The shift towards such a scenario may expose the communication and the CEMS critical components,
to attacks. For instance, an attacker can be:
a hacker with no intent to cause damage and who is satisfied by the penetration of systems
accessible through the Internet;
a criminal (e.g., disgruntled employee of the Energy Supplier or Energy Service Provider) who wants
to cause financial loss to the customer or to the energy service provider;
a customer with malicious objectives, e.g., to tamper the system with fraud purposes.
The attack can be executed either from the Internet or from a device connected to the HAN which
has been previously tampered, such as a personal computer or the LNAP, and may have special
information or authorizations (e.g., EMG login credentials, remote management of home automation
devices).
All in-house components are assumed to be connected to the CEMS. Among the functionalities of the
CEMS depicted in the use case diagrams (see Figures 20-25), the most critical operations that must
be secured are: i) direct load/generation management (DG.01.01) and ii) communication of power
consumption information (DG.03.01). The considered misuse cases are depicted in Figure 21.
consumption
Scenario AMR
Measurement (MM)
Scenario Name : Reference:
MM.01.01 - The metering system finds the request to be
invalid
Ref. [4], subchapter 3.3
MM.01.01 - The metering system finds that the role fulfilled by
actor A does not have the necessary access rights
Ref. [4], subchapter 3.3
MM.02.01 - System finds the data nor plausible or missing Ref. [5], subchapter 3.2.2
Customer information provision (CI)
CI.01 Provide information to consumer Ref. [8], subchapter 3.4
Collect AMI events and status information (ES)
ES.02 Manage supply quality Ref. [7], subchapter 3.3
Scenario CEMS
Demand and Generation flexibility for technical and commercial operations (DG)
DG.01 Direct load / generation management
DG.02 HL-UC Flexibility offerings
Ref. [14]
Ref. [16]
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Figure 117:Mis-use diagrams for the considered CEMS functionalities
The alteration or missed delivery of load adjustment commands that can be performed by means of
active attacks, i.e., the attacker tries to alter system resources or affect their operations. This may
compromise the capability of the customer to use the smart appliances or even the execution of
emergency procedures Figure 104 When the attacker is able to compromise a limited number of
CEMS the impact of the attack is low; however, when the attack is coordinated and several CEMS
systems are compromised (e.g., more than 100) or when some critical CEMS are violated (e.g., police
and fire departments systems) the impact of the attack can range from moderate to high (e.g., when
the CEMS systems of a very extended area, such as a city, are all compromised in a limited interval of
time). In the following we refer to this misbehaviour as incorrect direct load generation management,
mis-use case DE.01 (see Figure 21).
The access to power consumption/generation data shall also be secured against non-authorized
accesses. In other words customer power-related data shall be protected against passive attacks, i.e.,
attempts to learn or make us of information from a system without affecting its resources. As a
matter of fact, this is mandatory according to privacy law in some countries of the European
Community, such as Germany. Moreover, sophisticated burglaries could be architected when such
information is not secured. For example, thieves can exploit power consumption data to infer when
persons are not in the buildings and then plan physical penetrations. The impact of such an attack
can be classified as low. In the following we refer to this misbehaviour as disclosure of power
consumption information, DE.02 (see Figure 21).
For the aforementioned motivation, the network security requirements that shall be guaranteed in
CEMS systems are confidentiality, integrity and availability. In particular, for the communication of
direct load/generation management operations (i.e., load and emergency commands) integrity and
availability shall be guaranteed; while confidentiality, integrity and availability shall be assured when
power consumption data are exchanged.
According to the CEMS logical architecture described in Section 1 the most critical components
involved in the aforementioned operations are the EMG and the CEMS. Indeed, these can be
connected to the home WiFi and the likelihood to be exposed to malicious attacks is higher with the
respect to the components that are in dedicated network and when not protected by firewall or
other security mechanisms (e.g., encryption).
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Incorrect Direct load and generation management (DE.01)
The considered active attacks that compromise the integrity and/or the availability of EMG/CEMS
and lead to incorrect direct load generation management, are:
Man In the Middle (MIM) – an opponent captures messages exchanged between the EMG
and the CEMS. It can partially alter the content of the messages, or the messages are delayed
or reordered to produce an unauthorized effect.
Masquerade – an opponent sends fake messages the EMG pretending to be a different
entity.
Denial of Service (DoS) – the attacker floods anomalous messages to the EMG. It prevents or
inhibits the normal use or management of the communication facilities and/or the
components.
These attacks have been selected since they are usually performed by exploiting the most commonly
computer system and network vulnerabilities (e.g., sensitive data exposure, insecure object
references, broken authentication and session management, security misconfiguration). MIM and
Masquerade attacks can violate both integrity and availability; while, DoS violates only availability.
Tables Scenario D.01.01-D.01.03 detail the considered active attack scenarios. It is worth noting that
just one interaction is considered for the mis-use cases DG.01.01 and DG.03.01; in particular, it is
assumed that the Actor D starts the communication. However, a similar analysis can be applied when
Actor A initiates the communication.
The step by step description of the MIM attack is also explained for the sake of clarity. As for other
attacks (i.e., masquerade and DoS) the explanations can be extracted from the Description of
Process/Activity field.
Scenario DE.01.01
Scenario Name: MIM
Step
No.
Event Name of
Process /
Activity
Description of
Process/Activity
Service Information
Producer
Information
Receiver
Information
Exchanged
Technical
Require-
ments R-
ID
1 Attacker
captures
a
message
that
wants to
alter
MIM – load
command
interceptio
n
The attacker
intercepts and alters
a load adjustment
command sent by
the EMG
Load
Manage
ment
EMG Attacker Load
management
command
2 Attacker
replies an
altered
load
message
MIM –
sending
altered
load
command
The attacker
modifies the
message
intercepted at step
1 and then sends it
Load
Manage
ment
Attacker CEMS Altered load
management
command
3 Attacker
captures
the reply
to the
previousl
y altered
message
MIM –
interceptin
g and
altering
expected
change
message
The attacker
intercepts and alters
the expected
change message
(i.e. the reply to the
load adjustment
command )
Expected
change
CEMS Attacker Expected
change
message
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Figure 118 Mis-sequence diagram for the MIM attack
The MIM attack assumes an adversary can (i) observe messages exchanged, (ii) intercept messages
and (iii) reply messages with altered content (e.g., a load adjustment command sent by the EMG).
The attack takes place when the adversary intercepts the load adjustment command sent by the
EMG. Then, the attacker modifies the message previously intercepted (step 2 in Table Scenario
DE.01.01) and sends it to the CEMS. The CEMS is not aware of the adversary modification and takes
the load adjustment command as appropriate and reply to the message. Hence, the attacker
intercepts and alters the expected change message sent by the CEMS (i.e. the reply to the load
adjustment command) and finally sends the altered message to the EMG. In this scenario, it is
assumed that the CEMS sends the response message to the EMG. However, the attacker might also
be able to redirect all messages sent by the CEMS to himself, e.g., by means of DNS tempering.
4 Attacker
replies an
altered
expected
change
message
MIM –
sending
altered
expected
change
message
The attacker sends
the message altered
at step 3
Expected
change
Attacker EMG Altered
expected
change
message
Scenario DE.01.02
Scenario
Name:
Masquerade
Step
No.
Event Name of
Process /
Activity
Description of
Process /
Activity
Service Information
Producer
Information
Receiver
Information
Exchanged
Technical
Require-
ments R-
ID
1 Attacker
sends a
fake
message
Masquerade –
sending fake
load
adjustment
The attacker
pretending to be
an authorized
entity (e.g.,
Load
Manage-
ment
Attacker EMG Fake load
management
command
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command energy service
provider) sends a
fake load
adjustment
command
2 The EMG
receives
the load
adjust-
ment
com-
mand
EMG – sending
load
management
command
The EMG believes
the message
received at step 1
was transmitted
by an authorized
entity and it
forwards the load
management to
CEMS
Load
Manage-
ment
EMG CEMS Altered load
management
command
3 CEMS
receives
the load
managem
ent
command
from
EMG
CEMS – sending
the load
management
command
CEMS sends the
start of load
management
notification to
Display
Visualizat
ion of
load
manage-
ment
CEMS Display Load
management
command
4 CEMS
receives
the load
managem
ent
command
from
EMG
CEMS – sending
load
adjustment
CEMS - decides
which Smart
Appliances needs
to be adjusted
and sends an
order of load
adjustment to the
Smart Appliances
/ generators
Load
Manage
ment
CEMS Smart
Appliances /
generators
Order of load
adjustment
5 Smart
Appliance
s /
generator
s receive
the order
of load
adjustme
nt
Smart
Appliances /
generators –
sending
adjustment
feedback
The Smart
Appliances /
generators decide
to switch on/off
based on the
consumer’s
settings and send
feedback to CEMS
Load
Manage
ment
Smart
Appliances /
generators
CEMS Load
adjustment
feedback
6 CEMS
receives
feedback
from
smart
appliance
s /
generator
s
CEMS – sending
change
consumption
CEMS informs
EMG on which
change in
consumption to
expect.
Load
Manage
ment
CEMS EMG Change in
consumption
7 EMG
receives
the
change in
consumpt
ion from
CEMS
EMG – sending
change
consumption
EMG forwards the
change in
consumption to
what it believes is
the authorized
entity
Load
Manage
ment
EMG Attacker Change in
consumption
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Figure 119: Mis-sequence diagram for the Masquerade attack
Scenario DE.01.03
Scenario Name: DoS
Step
No.
Event Name of
Process /
Activity
Description of
Process /
Activity
Service Information
Producer
Information
Receiver
Information
Exchanged
Technical
Require-
ments R-ID
1 Attacker
replies an
altered
load
message
DoS – sending
anomalous
message
The attacker
sends an
anomalous
message to the
EMG
- Attacker EMG Anomalous
management
command
N Attacker
replies an
altered
load
message
DoS – sending
anomalous
message
The attacker
sends an
anomalous
message to the
EMG
- Attacker EMG Anomalous
management
command
N+1 Actor D
sends an
emergency
load
adjustment
command
Impossibility
to receive the
emergency
load manage-
ment
procedure
The EMG is
overloaded due
anomalous
messages
received by the
attacker
Emer-
gency
load
manage-
ment
Actor D - Emergency
load
management
command
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Figure 120 Mis-sequence diagram for the DoS attack
Disclosure of power consumption information (DE.02)
In this section the focus is on passive attacks that compromise the confidentiality of power
consumption information exchanged between the EMG and the smart appliances. As for the active
attacks that compromise the integrity and availability, similar analyses performed for the mis-use
case DE.01 also apply for the power consumption communication.
The considered passive attacks that compromise confidentiality are:
Release of message content: the opponent tries to eavesdrop transmissions;
Traffic analysis: the opponent observes the pattern of the messages to discover the location
and the identity of the parties involved in the transmissions, and the frequencies and the
length of exchanged messages.
Scenario DE.02.01
Scenario Name: Release of message content
Step
No. Event Name of
Process /
Activity
Description of
Process /
Activity
Service Informa-
tion
Producer
Informa-
tion
Receiver
Information
Exchanged
Technical
Require-
ments R-
ID
1 New
consumption
/ generation
information is
available for
the SA/
generator
SA/Gen –
sending new
power-
related
information
Smart appliance
/ generator
sends
information
regarding
consumption to
the CEMS
SA Power
consumption
/ generation
information
SA /
generator
CEMS Individual
appliance
consumption
/ generation
2 CEMS
received
CEMS –
sending new
The CEMS
aggregates
House power
consumption
CEMS Display Total and/or
forecasted
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Figure 121: Mis-sequence diagram for the Disclosure of message attack
Table Scenario DE.02.01 details the disclosure of message content scenario. When the smart
appliance / generator sends information regarding consumption to the CEMS, the CEMS aggregates
and/or forecasts total consumption and sends this information to the display and to the EMG. The
consumption
/ generation
information
per individual
appliance
house power-
related
information
and/or
forecasts total
consumption
and sends this
information to
the display
/ generation
information
house
consumption
/ generation
3 CEMS
received
consumption
/ generation
information
per individual
appliance
CEMS –
sending new
house power-
related
information
The CEMS
aggregates
and/or
forecasts total
consumption
and sends this
information to
the EMG
House power
consumption
/ generation
information
CEMS EMG Total and/or
forecasted
house
consumption
/ generation
4 The attacker
intercepts the
message
Attacker –
reading
house power-
related
information
The attacker
intercepts the
message and
reads the
content about
power
consumption/
generation
House power
consumption
/ generation
information
SA
/generator
Attacker Total and/or
forecasted
house
consumption
/ generation
5 EMG received
(forecasted)
consumption
/ generation
EMG –
sending new
house power-
related
information
EMG forwards
information to
Actor D
House power
consumption
/ generation
information
EMG Actor D Total and/or
forecasted
house
consumption
/ generation
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attacker may intercept the message and if no cryptography method is used he/she reads the content
about power consumption/ generation.
As for the traffic analysis attack the only differences with respect the attack depicted in Figure 29
(i.e., the scenario DE.02.01) is that we are assuming that the adversary cannot understand the
message. Hence, the opponent needs to intercept several messages in order to observe the
communication pattern and discover relevant information (e.g., location and the identity of the
parties involved in the transmissions).
10.4.5 Information Exchanged
Information Exchanged
Name of Information
Exchanged
Description of Information Exchanged Requirements to information data R-ID
Metering – Metering Values
(periodically)
Metering – Metering Values
(aggregated)
Metering – Metering Values (Billing)
Metering – Parameter
Sub Metering – Metering Values
(periodically)
Sub Metering – Parameter
Control – Switching Command
Control – Status Information
Control – Parameter
10.4.6 Common Terms and Definitions
Common Terms and Definitions
Term Definition
AC Air Conditioning Unit
AMI Advanced Monitoring Infrastructure
AMR Automated Meter Reading
Cellular Network Cellular Network
CEMS Customer Energy Management System
CHP Local CHP
CI Customer Information
CLS Controllable Load System
DER Distributed Energy Resource
DG Distributed Generation
DNO Distribution Network Operator
DoS Denial of Service
DSM Demand Side Management
ES Events and Status
ESP Energy Service Provider
FLIR Fault Location, Isolation and Restoration
HAN Home Area Network
EMG Energy Management Gateway
HES Head End System
ICT Network Communication Network
LNAP Local Network Access Point
MDA Metering Data Aggregator
MDMS Meter Data Management System
MIM Man In the Middle
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MM Measurement
MO Meter Operator
NAN Neighbourhood Area Network
NNAP Neighbourhood Network Access Point
Power Grid Power Grid
RES renewable energy sources
SM Smart Metering
SSM Supply Side Management
UI User Interface
WAN Wide Area Network
Communication Hub
Control Hub
Household Appliance
Power Predictor
Control Entity
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11 Annex C - Table of Requirements
This annex contains the list of Requirements with the mapping on the project WP where are addressed.
Considering the priority of the Requirements these are marked as follows:
Now (the requirement is taken into serious consideration inside the project)
Wish (the requirement is considered desirable but not yet scheduled in the project activities)
Future (to be considered at some point in time)
11.1 Requirements for Medium Voltage Control Use Case
Requirement ID
Title Description WP2 WP3 WP4 WP5 WP6
System Level Requirements
Architectural
REQ_001 Number of primary substation per center
Each center controls <min,max> primary substations.Min, max values depend on the specific topology of the telecontrol grid. In the scenario addressed in SmartC2Net Min=20, Max = 100, Avg=60
x x
REQ_002 Grid topology Per each substation includes all the topological parameters, e.g. number of HV/MV transformers (i.e. n=2), number of MV lines(i.e. n=12), number of DER per MV line (i.e.n=10), number of MV loads per MV line(i.e. n=60/100), number of Secondary Substations per MV lines(i.e. n=40/100)
x x
REQ_003 Hosting capacity <0,15>MW generated by DERs connected to the MV lines of a primary substation
x x
Communication
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Requirement ID
Title Description WP2 WP3 WP4 WP5 WP6
REQ_004 DER network availability Any DER communication link should be available 8755 hs / year
x x
REQ_005 Compliance with standards The VC communications will be compliant with standard protocols, if available
x x x x
Dependability
REQ_006 Control infrastructure reliability and availability
The communication infrastructure for control operations should be available with a value of at least 99.999%(*) (Center -Substation communication) and 99.95 (DER- Substation communication) (*) This very restrictive requirement is meant to highlight that the availability needs to be near 100% on each time instant
x x
REQ_007 Control infrastructure redundancy
The communication infrastructure for control operations should use redundant heterogeneous communication links as backup solutions to fault tolerance
x x
Security
REQ_008 Control infrastructure security
The communication infrastructure for control operations should guarantee protection against intentional threats
x x
REQ_009 ICT maintenance Remote ICT maintenance activity to substation devices does not adversely affect the VC operation
x
REQ_010 ICT maintenance logging Remote ICT maintenance actions to substation devices are logged
x
Use Case Level Requirements
Communication
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Requirement ID
Title Description WP2 WP3 WP4 WP5 WP6
REQ_011 DER network heterogeneity Due to differences in the geographical coverage of communication technologies the VC shall work with heterogeneous DER networks (e.g., wired, wireless)
x x
REQ_012 Substation-DER data communication
The Substation - DER communication main measures are: bandwidth (i.e. 10 - 56 Kbps), data rate (i.e. measurements every 2 seconds)
x x x x
REQ_013 Centre-Substation data communication
The Center - Substation main measures are: bandwidth (i.e. 10 kbps), data rate (i.e. generation forecast update every 12 hours)
x x x x
REQ_014 Frequency of radio-based substation-DER communications
frequency band, i.e. in Europe LTE allowed frequencies are 800, 900, 1800, 2600 MHz and band numbers are 3, 7, 20
x x
REQ_015 Centre-Substation transmission time
end-to-end transmission delay (i.e. 20 ms-2 sec) x x x
REQ_016 Substation-DER transmission time
end-to-end transmission delay (i.e. 20 ms-15 sec) x x x
Functional
REQ_017 Control loop The control loop is triggered by critical events (e.g. under/over voltage event, TSO request, grid topology change). In absence of criticalities, the VC function is executed on a periodic base (e.g. every 15 minutes) for optimization purposes.
x x
REQ_018 Time out of voltage bound violation
<n> unit of time allowed to be out of voltage ranges (i.e. max frequency n= 0.1 sec 50.3 Hz (restrictive range), n=1.0 sec 51.5 Hz(permissive range). Min frequency n=0.1 sec 49.7 Hz (restrictive range), n=4.0 sec 47.5 Hz (permissive range))
x
REQ_019 Voltage deviation +/- 10% Vn x
Performance (Quality of Service)
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Requirement ID
Title Description WP2 WP3 WP4 WP5 WP6
REQ_020 Refresh Time of the DMS Operator HMI
The data values on the central operator interface are refreshed every 2 seconds
x x
REQ_021 Response Time The response time of the VC closed control loop, from the command issue to the end of the set point actuation, including the transmission time and the actuation time. It depends on actuation time constants of OLTC and DER power electronics. It is of the order of seconds
x
REQ_022 OLTC Actuation Time The time taken by OLTC for actuating a set point is 3 seconds
x x
REQ_023 Inverter Actuation Time The time taken by the inverter for actuating a set point is 1-2 seconds
x x
REQ_024 Synchronisation Time The substation and DER controllers provide functionality to synchronise their internal clock
x
Standard/Regulation
REQ_025 DER power wrt grid voltage Norm CEI 0-16 P < 0.1 MW: plants are connected to the LV grids 0.1 MW < P < 0.2 MW: plants may be connected either to the LV or to the MV grids 0.2 MW < P < 3 (6 in case of generation) MW: plants are connected to the MV grids 3 (6 in case of generation) MW < P < 10 MW: plants may be connected either to the MV or to the HV grids 10 MW < P < 100 MW: load plants are connected to the HV grids 10 MW < P < 200 MW: generation plants are connected to the HV grids
x x
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Requirement ID
Title Description WP2 WP3 WP4 WP5 WP6
REQ_026 DER communication systems
Norm CEI 0-16 In order to allow the evolution of distribution grids towards smart grids, it is necessary that all active customers are endowed with a communication system allowing the (real time) data exchange with the DSO. This will allow the DSO to implement optimization logics and to send all customers the signals implementing the actions (e.g. disconnection) needed to guarantee the security of the whole power system.
x x
Component Level Requirements
Architectural
REQ_027 Substation Network Integrity
In order to support the operation integrity of substation systems the communication interfaces in the substation devices have to be limited to essential functions
x
Communication
REQ_028 Ordered data streams The VC algorithm requires the undisturbed execution of acquisition and actuation sequences based on orders flows of status, events and commands
x
REQ_029 Load Forecast Transmission Rate
Load profiles are transmitted every 12 hours x x
REQ_030 Generation Forecast Transmission Rate
Generation forecasts are transmitted every 12 hours x x
REQ_031 Cost Transmission Rate Cost data are transmitted every 1 hour x x
REQ_032 Range of substation-DER communications
The DER-substation distance is within the range of the MV line length, in the order of 5 Km
x x
Functional
REQ_033 Generation Forecast Time Horizon
Active power production plans are given for 36 hours x x
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Requirement ID
Title Description WP2 WP3 WP4 WP5 WP6
REQ_034 Generation Forecast Time Resolution
Active power production plans are given with resolution of 1 hours
x x
REQ_035 Generation Forecast Update Rate
Active power production plans are updated every 12 hours
x x
REQ_036 Load Forecast Time Horizon Load plans are given for 36 hours x x
REQ_037 Load Forecast Time Resolution
Load plans are given with a resolution of 1 hours x x
REQ_038 Load Forecast Update Rate Load plans are updated every 12 hours x x
REQ_039 Cost Update Cost values are updated every 1 hour x x
Standard/Regulation
REQ_040 End-to-End communication integrity
IEC 62351 Part 3 End-to-end integrity of VC communications should be guaranteed through an appropriate configuration of the TLS protocol
x x x
REQ_041 Message Authentication IEC 62351 Part 6 Message authentication of VC communications will follow the standard indications for the specific protocol
x x x
Security
REQ_042 Integrity of transmitted data Transmitted data/measurements/commands are protected against intentional changes (Integrity of transmitted data is preserved in all data exchanges)
x x x
REQ_043 Integrity of stored data Stored data/measurements are protected against intentional changes
x x x
REQ_044 Action authorization Data are available to authorized actions only x x x
REQ_045 Authenticity of data Authenticity of data/measurements/commands is ensured
x x x
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Requirement ID
Title Description WP2 WP3 WP4 WP5 WP6
REQ_046 Communication logging Appropriate logs of VC application messages are made available
x x x
Table 5 Requirements for Medium Voltage Control Use Case
11.2 Requirements for EV Charging Use Case
Requirement ID
Title Description WP2 WP3 WP4 WP5 WP6
System Level Requirements
Architectural
REQ_200 Aggregator interaction The charging station has to report the aggregated demand, and the aggregator has to provide energy price information.
x
REQ_201 Meter aggregation
In order to realize the decentralized architecture, it is required that all the smart meters readings for households, charging station (aggregated metering), PV production and battery storage in that LV grid can be queried, forwarded or stored by the LV grid controller from a meter aggregation component.
x
x
Functional
REQ_202 Demand response The demand management control target of reducing for example the load in a LV by x% must affect the setpoints calculated by the MV controller accordingly.
x
REQ_203 Charging station reaction to local load increase or production decrease
sudden reduction of the available power in a charging station has to reduce the energy amount (not below the minimum) and the charging duration accordingly
x x
Interface
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Requirement ID
Title Description WP2 WP3 WP4 WP5 WP6
REQ_204 Interface LV controller-charging controller
the LV grid controller and the charging controller have to be able to exchange asynchronous unidirectional messages
x
REQ_205 Aggregator connection Each charging station must interact with an aggregator (aggr. Charging infrastructure manag.)
x
REQ_206 LV Grid-MV grid interface
The MV controller must be able to set setpoints on the LV controllers as a part of the VC goal and to determine P and Q injected, based on the flexibility reported by the LV controller
x x
Use Case Level Requirements
Architectural
REQ_207 Charging spots Charging spots are controlled either by the EMS (home scenario) or by a charging station controller
x
REQ_208 Routing and reservation The routing and reservation service must select the charging station and allocate charging resources to approaching EVs.
x
Interface
REQ_209 EV demand flexibility
An EV has to provide the charging station following demand flexibility data: plug-in time or an estimate of it, minimum amount of energy, maximum amout (full charging) , charging speed supported by the EV. It MAY provide the estimated parking duration.
x
REQ_210 Routing and reservation Charging stations have to report their load forecasts to the routing service, and would receive reservation requests.
x
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Requirement ID
Title Description WP2 WP3 WP4 WP5 WP6
REQ_211 EV connectivity with reservation service
The EV has to communicate wirelessly with the reservation server.
Standard/Regulation
REQ_212 Charging speeds
The charging power can vary from zero up to a maximum charging power supported by both the charging spot and the vehicle
x
Component Level Requirements
Communication
REQ_213 Metering Network Monitoring
Metering network disfunction has to be recognized at the LV grid controller
x
REQ_214 LVcontroller-CS controller link monitoring
A connection disruption of the link LVGC to CS Controller has to be identified
x x
REQ_215 Control links to charging points monitoring
Communication disfunction of a charging point connection has to be identified
Functional
REQ_216 Charging station controller function
The charging station has to be able to calculate/estimate at any point in time the current and the future EV charging demand (time horizon of 6 hours for instance)
x
REQ_217 Charging schedule A charging station maintains a plan (schedule) for all known charging jobs, which is updated in case of event updates.
x
REQ_218 Meter readings The meter reading interval for some components is as low as 1 second.
x x
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Requirement ID
Title Description WP2 WP3 WP4 WP5 WP6
REQ_219 PV control Sudden increase of LV voltage at a PV generation bus has to be corrected by controlling signal from the LV controller to the PV inverter in a matter of X seconds
x x
REQ_220 Interface between car and CP
The EV should provide periodical energy flexibility profile (min and max). This may go beyond the interface specified in IEC15118
x
Security
REQ_221 Secure channel The communication between LVGC and charging stations shall be secured (encrypted, authenticated, etc.)
x
Table 6 Requirements for EV Charging Use Case
11.3 Requirements for External Generation Use Case
Requirement ID
Title Description WP2 WP3 WP4 WP5 WP6
System Level Requirements
Communication
REQ_400 Access network RTT measurements
Up-to-date Round Trip times measurements of the AN shall be available to the LVGC as well as the assets. RTT estimations shall be expressed in ms.
x x x
REQ_401 Access network throughput measurements
Up-to-date throughput measurements of the AN shall be available to the LVGC as well as the assets. Throughput estimations shall be expressed in bps.
x x x
REQ_402 Access network packet loss probability measurements
Up-to-date packet loss probability measurements of the AN shall be available to the LVGC as well as the assets. Packet loss probability estimations shall be expressed in %.
x x x
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Requirement ID
Title Description WP2 WP3 WP4 WP5 WP6
REQ_403 Access network connectivity measurements
Up-to-date connectivity measurements of the AN shall be available to the LVGC as well as the assets. Connectivity estimations shall be expressed as boolean.
x x x
REQ_404 Access network reconfiguration access
SmartC2Net platform should be able to reconfigure the AN network layers down to the data link layer.
x x
REQ_405 Provisioning of meta quality data of accessed data
The ITC system shall be able to provide meta data that indicates the reliability of the data being provided
x x x
Functional
REQ_406 Voltage variations The voltage profile in LV and MV feeders shall not exceed +/- 10% from the rated value as a 10 min average value. This is stated in DS/EN 50160 and in the Danish Recomedation 16 - Voltage Quality in LV grids.
x
REQ_407 Voltage dips/swells A voltage dip is not allowed to exceed -5% from the rated nominal value. A voltage swell is not allowed to exceed +5% from the rated nominal value. This is stated the Danish Recomedation 16 - Voltage Quality in LV grids. A voltage dip or swell is a rapid decrease or increase in voltage from one sample to the next. This is stated in DS/EN 50160 and in the Danish Recomedation 16 - Voltage Quality in LV grids.
x
Dependability
REQ_408 Resilient network performance operation
Even during network performance degradation, the system shall be able to continue without major loss of control
x x x
REQ_409 Reliable middleware components
Developed middleware components shall be operational to the extend that the components themselves will not fail during tests
x x x
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Requirement ID
Title Description WP2 WP3 WP4 WP5 WP6
Component Level Requirements
Communication
REQ_410 Aggregation of Available Reactive Power
Aggregation of available reactive power shall be computed at secondary substation level. This algorithm shall consider the status and available power from flexible assets in LV feeders.
x x x
Functional
REQ_411 Individual Setpoint for active power - Asset
All flexible assets in MV/LV grids shall be able to receive and follow an admissible setpoint for active power from upper hierarchical controller(s). A positive sign means power injection into the grid while a negative sign means power consumption. This setpoint shall be expressed in [kW].
x x x x
REQ_412 Individual Setpoint for reactive power - Asset
All flexible assets connected through a power converter to MV/LV grids or having reactive power control capabilities shall be able to receive and follow an admissible setpoint for reactive power from upper hierarchical controller(s). A positive sign means power injection into the grid while a negative sign means power consumption. This setpoint shall be expressed in [kVAR].
x x x x
REQ_413 Available active power - Asset
All flexible assets in MV/LV grids shall be able to send information about available active power to upper hierarchical controller(s). This availability shall be defined as the difference from rated/potential active power of the device and the actual production/consumption. A positive sign means power injection into the grid while a negative sign
x x x x
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Requirement ID
Title Description WP2 WP3 WP4 WP5 WP6
means power consumption. The signal shall be expressed in [kW].
REQ_414 Available reactive power - Asset
All flexible assets connected through a power converter to MV/LV grids or having reactive power control capabilities shall be able to send information about available reactive power to upper hierarchical controller(s). A positive sign means power injection into the grid while a negative sign means power consumption. The signal shall be expressed in [kW].
x x x x
REQ_415 Active Power Production - Asset
All flexible assets in MV/LV grids shall be able to send information about active power production to upper hierarchical controller(s). A positive sign means power injection into the grid while a negative sign means power consumption. This signal shall be expressed in [kW].
x x x x
REQ_416 Reactive Power Production - Asset
All flexible assets connected through a power converter to MV/LV grids or having reactive power control capabilities shall be able to send information about reactive power production/consumption to upper hierarchical controller(s). A positive sign means power injection into the grid while a negative sign means power consumption.The signal shall be expressed in [kVAR].
x x x x
REQ_417 Voltage measurements - Asset
All flexible assets in MV/LV grids equipped with voltage measurement devices at their Point of Connection (PoC) shall be able to provide measurement of voltage in PoC to upper hierarchical controller(s). This measurement signal shall be expressed in [V].
x x x x
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Requirement ID
Title Description WP2 WP3 WP4 WP5 WP6
REQ_418 State-of-Charge - Asset Energy storage systems connected to MV/LV grids shall provide to upper hierarchical control levels a signal reflecting their State-of-Charge (SoC). This signal shall be expressed in [%] based on the energy storages rated capacity.
x x x x
REQ_419 Setpoint for active power - LVGC
LVGC shall be able to receive and follow an admissible setpoint for active power received from MVGC. These setpoints shall be expressed in [kW].
x x x x
REQ_420 Setpoint for reactive power - LVGC
LVGC shall be able to receive and follow a setpoint for reactive power received from MVGC. These setpoints shall be expressed in [kVAR].
x x x x
REQ_421 Active power control - LVGC LVGC shall be able to control active power on MV side of the secondary substation. The active power control shall be made using the Setpoint from MVGC, measured active power from assets in LV grids as well as the total available power from the LV assets. The output of the active power control shall be a reference signal for the all flexible assets connected to LV feeders. in [kW].
x x
REQ_422 Active power dispatch - LVGC
LVGC shall be able to distribute the reference signal from active power control to flexible assets in LV grids as individual setpoints for active power. The individual setpoints for active power shall take into account actual power production and availability from the flexible assets . These individual setpoints signal shall be expressedin [kW].
x x
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Requirement ID
Title Description WP2 WP3 WP4 WP5 WP6
REQ_423 Reactive power control - LVGC
LVGC shall be able to control reactive power on MV side of the secondary substation. The reactive power control shall be made using the reactive power setpoint from MVGC or the reactive power reference from Voltage Control in LVGC, measured reactive power from flexible assets in LV grids as well as the total available power from the LV assets. The output of the reactive power control shall be a reference signal for the all flexible assets connected to LV feeders. This reference signal shall be expressed in [kVAR].
x x
REQ_424 Reactive power dispatch - LVGC
LVGC shall be able to compute and distribute the reference signal from reactive power control in LVGC to flexible assets in LV grids as individual setpoints for reactive power. The individual setpoints for reactive power shall take into account actual reactive power production and availability from the flexible assets . These individual setpoints signal shall be expressed in [kVAR].
x x
REQ_425 Aggregation of Available Active Power
Aggregation of available active power shall be computed at secondary substation level. This algorithm shall consider the status and available power from flexible assets in LV feeders.
x x x
Table 7 Requirements for External Generation Use Case
11.4 Requirements for AMR and CEMS Use Case
Requirement ID
Title Description WP2 WP3 WP4 WP5 WP6
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Requirement ID
Title Description WP2 WP3 WP4 WP5 WP6
System Level Requirements
Architectural
REQ_600 CEMS communication functionalities extensibility
The CEMS shall be extensible for the implementation of further / future communication functionalities
REQ_601 CEMS integrity The components of the CEMS shall be limited to the minimal necessary functionality to avoid costs and security risks
x x x x x
Communication
REQ_602 Home network heterogeneity
The CEMS shall work with heterogeneous home area network (e.g., wired, wireless)
x x x x x
REQ_603 Home network conditions heterogeneity
The CEMS shall work in variable network conditions (e.g., available bandwidth, delay, packet loss)
x x x
REQ_604 Cost Transmission Rate Cost data are transmitted every <n> time intervals x x
Functional
REQ_605 Smart Meter reading The smart meter periodically or on request provides meter readings and complete state and logging information.
x x x x x
REQ_606 EMG metering data computation
The EMG shall apply any necessary pre-computation on the local metering data (if applicable)
x x
REQ_607 EMG load shifting The EMG shall be able to issue commands for load shifting when allowed and possible, as requested by the HES
x x
REQ_608 Tariff information updates The CEMS shall be provided with actual tariff information in intervals of <n> / on tariff change
x x x
Interface
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Requirement ID
Title Description WP2 WP3 WP4 WP5 WP6
REQ_609 Control gateway network interfaces
The CEMS energy control sub-system shall have both WAN network interface and HAN interface
x x x
REQ_610 Metering Gateway network interfaces
The metering gateway sub-system shall have a WAN network interface as well as an interface with HAN
x x x
REQ_611 DER communication The CEMS / AMR house network shall allow the communication with house related DER
x x x
REQ_612 Flexible loads communication
The CEMS house network shall allow the communication with house related flexible load
x x x
REQ_613 User interaction system communication
The CEMS house network shall allow the communication with the house related user interaction subsystem (e.g., the external consumer display)
x x x
REQ_614 Metering Data Aggregation communication
The Smart Meter shall interface with the HES x x x
REQ_615 Aggregation communication The CEMS / AMR shall interface with the Aggregator (i.e., the Flexible load and DER aggregation) for controlling purpose
x x x x
REQ_616 CEMS Network communication
The CEMS shall interface with the communication network
x x x
REQ_617 CEMS power grid interface The CEMS shall interface with the power grid operator x x x x x
REQ_618 CEMS metering communication
The CEMS shall interface with the metering operator x x x x x
REQ_619 Private vehicle charging spot interaction
The CEMS house network shall allow the communication with private vehicle charging spots
x x x
REQ_620 CEMS and home automation communication
The CEMS house network shall allow the communication with home building automation
x x x
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Requirement ID
Title Description WP2 WP3 WP4 WP5 WP6
equipment
REQ_621 Smart Meter EMG connection
Smart meter and EMG might interface if not prohibited due to legal ruling
x x x
Dependability
REQ_622 Control infrastructure availability
The communication infrastructure for control operations should be highly available
x x x
REQ_623 Control infrastructure reliability
The communication infrastructure for control operations should be reliable
x x x
REQ_624 Energy Management Gateway reliability
The EMG shall have an availability of 99% x x x x x
REQ_625 Smart Meter availability The Smart Meters shall be available 99% of the year x x x x x
REQ_626 CEMS reliability The components of the CEMS shall possess a MTBF equal or greater than <n>
x
Performance (Quality of Service)
REQ_627 Intrusion detection false alarm rate
False positives in signaling the attempt to tamper the components and/or the communication shall be limited to a MAX_FP extent
x x x
REQ_628 Time Synchronization The EMG and Smart Meters shall be able to synchronize their clocks with the HES
x x
REQ_629 Metering Data Transmission The EMG / HES and Smart Meters shall be able to exchange metering data in intervals of down to 1 second / on demand
x x x
REQ_630 Access Point WAN Communication
The LNAP / NNAP shall provide a minimum data rate of approx. 20 Kbit/s per connected SM with a maximum Delay of 15 min.
x
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Requirement ID
Title Description WP2 WP3 WP4 WP5 WP6
REQ_631 Communication quality of service reports
The LNAP / NNAP shall monitor the quality of its WAN connection and report any deviation from normal operation to the EMG and HES
X x x x
Standard/Regulation
REQ_632 Compliance with standards The Communication Interfaces and Protocols shall be in compliance with standards wherever applicable
x x x x x
REQ_633 Usage data intervall The intervall in which customer usage information is supplied shall be in accordance with national regulations
x x x
Security
REQ_634 In-house message authentication
The messages exchanged between the components within the HAN that may exploit a shared medium (e.g. WiFi LAN) shall be secured against unauthorized accesses and modifications
x x x
REQ_635 WAN message authentication
The messages exchanged between the CEMS / AMR and external entities (e.g., Metering Aggregator) shall be secured against unauthorized accesses and modifications
x x x
REQ_636 house message confidentiality and privacy
The messages exchanged between the components on the customer shared network (e.g., Wi-Fi LAN) shall be secured against disclosure of information and traffic analysis
x x x
REQ_637 WAN message confidentiality and privacy
The messages exchanged between the CEMS / AMR and external entities (e.g., Metering Aggregator) shall be secured against disclosure of information and traffic analysis
x x x
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Requirement ID
Title Description WP2 WP3 WP4 WP5 WP6
REQ_638 Tamper and fraud detection / protection
The physical components of the CEMS / AMR shall be guarded against manipulation
x x
REQ_639 Software Security The EMG, Smart Meters and LNAP shall be robust against software attacks (for example no standard passwords)
x x x
REQ_640 Attack logging and reporting The EMG, Smart Meters and LNAP shall be able to report detected attacks and tempering attempts
x
REQ_641 Access logging Any access (especially remote ICT access) to the CEMS /AMR components shall be logged
X x
Table 8 Requirements of the AMR / CEMS Use Case
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12 Annex D - Table of KPIs
This annex contains the list of Key performance Indicators with the mapping on the project WP where are addressed.
Considering the scope of the KPI these are marked as follows:
DSO oriented
CSP oriented
CSO oriented
Aggregator oriented
Customer oriented
12.1 Key Performance Indicators for Medium Voltage Control Use Case
KPI_id KPI name Definition Goal WP2 WP3 WP
4 WP5
WP6
Power related KPIs
KPI_001 Unsupplied power Size of grid affected by an attack/fault 0 MW x
KPI_002 DER involved # DERs per HV/MV substation affected by an ICT attack/fault 0 x
KPI_003 Lines involved # MV lines per HV/MV substation affected by an ICT attack/fault 0 x
KPI_004 Loads involved # unsupplied MV loads per HV/MV substation affected by an ICT attack/fault 0 x
KPI_005 Substation involved # HV/MV substations per Control Centre affected by an ICT attack/fault 0 x
KPI_006 Energy losses Amount of lost energy Min value KWatt/h x
KPI_007 Grid Hosting Capacity Amount of RES power per MV line Max value MW x
KPI_008 Power Quality improvements Percentage reduction of voltage variations in MV lines Min value
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KPI_id KPI name Definition Goal WP2 WP3 WP
4 WP5
WP6
KPI_009 Grid events
# Overvoltages # Undervoltages # Topological changes Min value x
KPI_010 Power grid stability Deviation from optimal voltage profile Min value x
KPI_011 Integrity of measurements # Correct measurements Max value x
KPI_012 Integrity of state estimation # Correct state estimations Max value x
KPI_013 Correct setpoints computation # Setpoints computed correctly Max value x
KPI_014 Cost optimization DSO cost to obtain an optimize voltage profile Min value x
KPI_015 Correct setpoint receipt # Setpoints received correctly Max value x
KPI_016 Security gain_overvoltages # Overvoltages w/o security/ # Overvoltages with security Max value x
KPI_017 Security gain_undervoltages # Undervoltages w/o security/ # Undervoltages with security Max value x
KPI_018 Voltage value (V)
The actual voltage Vh(t) for each electrical component h at time t Setpoint value x
KPI_019 Active Power (P)
The actual active Ph(t) for each electrical component h at time t Setpoint value x
KPI_020 Reactive Power (Q)
The actual reactive Qh(t) power, for each electrical component h at time t. Setpoint value x
Communication related KPIs
KPI_021 Communication Network Availability Mean Time To Failure / Mean Time Between Failure
99,999% (5 minutes per year) for Control Center - Primary Substation communication 99.95% for x x x
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KPI_id KPI name Definition Goal WP2 WP3 WP
4 WP5
WP6
Primary Substation -DER communication
KPI_022 Fault Awareness Fault detection time Min value T (sec) x
KPI_023
Localization and Isolation Time Faster reaction time to grid faults and ICT attacks Min value T (sec) x
KPI_024 Security gain_measurements # Correct measurements received w/o security /# correct measurements received with security Min value x x x
KPI_025 Security gain_setpoints # Correct setpoints received w/o security /# correct setpoints received with security Min value x x x
KPI_026 Security gain_legal data rate Legal data rate w/o security / legal data rate with security Min value x x x x
KPI_027 Security gain_lost msgs (packets)
# Legal msgs (packets) lost with security /# legal msgs (packets) lost w/o security Min value x x x x
KPI_028 Security gain_discarded msgs (packets)
# Legal msgs (packets) discarded with security /# legal msgs (pakets) discarded w/o security Min value x x x x
KPI_029 Security gain_availability Availability w/o security /availability with security Min value x x x x
KPI_030 Security delay (Transmission) delay with security /# delay w/o security Min value x x x x
KPI_031 Security_IDS # Intrusion attempts detected Max value x
KPI_032 Security_prevention_illegal_action # Prevented illegal actions with security Max value x x
Generic KPIs
KPI_033 Population involved Percentage of people affected by an attack/fault 0%
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KPI_id KPI name Definition Goal WP2 WP3 WP
4 WP5
WP6
KPI_034 Satisfied requirements # Requirements satisfied Max value x x Table 9 Key Performance Indicators for Medium Voltage Control Use Case
12.2 Key Performance Indicators for EV charging Use Case
In Table 10 we list a number of performance indicators for the EV charging use case. With other words, running the scenario with a certain configuration of
energy demand, supply, topology, charging demand, presence of failures or not, daily prices, etc. will create a (unique) set of these performance indicators,
that should reflect the objectives of users, CSO, DSO, etc.
KPI_id KPI name Definition Goal WP2 WP3 WP4 WP5 WP6
Power related KPIs
KPI_200 Number of Grid Events Amount of grid events and type. [#] Types are:Over-current (line/trafo), Overvoltage (Bus), Undervoltage (Bus)
0 x
x
KPI_201 Severity of Grid Events relative value of a grid event: Over-current: I/I_max-1 (branch), Over-voltage: [U/U_max-1/ (Bus), Under-voltage: U_min/U-1 (Bus)
fraction <1 (0)
x
x
KPI_202 Renewable resource efficiency, general
Renewable energy fed into grid/ Renewable energy generated without curtailment
% x
x
KPI_203 EV Demand reduction control
Demand actual reduction/demand reduction target difference in % (0) x
x
KPI_204 accuracy of LV following MV set points
Accuracy of actual achieving the target P/Q using EV flexibility and PV control
difference in % x
x
Communication related KPIs
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KPI_id KPI name Definition Goal WP2 WP3 WP4 WP5 WP6
KPI_205 Degradation of power quality without meter data
Define degradation criteria (duration of operation without grid events, etc.) if flexibility/meter data is disrupted (CS or CEMS).
failure duration # of sampling periods x x
x
KPI_206 Degradation of power quality if LV grid controller - charging station fails
Define degradation criteria, if a charging station does not receive actuation from the LV controller for a duration
minutes max Value x x
x
KPI_207 Degradation if PV control network fails
Define degradation criteria in case CEMS with PV and storage does not receive actuation
minutes max Value x x
x
Economical related KPIs
KPI_208 charging load balancing among close charging stations
distribution of load =charged energy/available charging energy
variance 0
x
KPI_209 cost performance minimum cost of energy that could be achieved by the aggregator given the EV flexibility divided by actual CSO costs of energy constrained by the DSO
100% x
x
Generic KPIs
KPI_210 User satisfaction – Level of Service
Average over all EVs Charged energy/maximum requested energy [%].
100%
x
KPI_211 User satisfaction – Availability of Service
Number of served users/number of users requesting service 100%
x
Table 10 Key Performance Indicators for EV charging Use Case
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12.3 Key Performance Indicators for External Generation Use Case
KPI_id KPI name Definition Goal WP2 WP3 WP4 WP5 WP6
Power related KPIs
KPI_400 Voltage limits in LV and MV feeders
The voltage profile in LV and MV feeders shall not exceed +-10% from the rated value as a 10 min average value.
10%
x x
KPI_401 Rapid Voltage change limit in LV feeders
Rapid voltage changes should not exceed +-5% of the rated value.
5%
x x
KPI_402 Rapid Voltage change limit in MV feeders
Rapid voltage changes should not exceed +-4% of the rated value.
4%
x x
Communication related KPIs
KPI_403 Access network packet loss limit
The application layer packet loss probability shall be low enough to allow the LVGC to adhere to its voltage limits.
<0.01 %* x x
x
KPI_404 Wide area network packet loss limit
The application layer packet loss probability shall be low enough to allow the MVGC to adhere to its voltage limits.
<0.01%* x x
KPI_405 Access network delay limit The application layer packet delay shall be low enough to allow the LVGC to adhere to its voltage limits.
<1 ms* x x
x
KPI_406 Wide area network delay limit
The application layer packet delay shall be low enough to allow the MVGC to adhere to its voltage limits.
<1 ms* x x
Table 11 Key Performance Indicators for External Generation Use Case
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12.4 Key Performance Indicators for AMR and CEMS Use Case
The Key Performance Indicators (KPI) of the AMR and CEMS use case are listed in Table 12
KPI_id KPI name Definition Goal WP2 WP3 WP4 WP5 WP6
Power related KPIs
KPI_600
Accuracy of energy consumption measurement / estimation
Accuracy of energy consumption measurement / estimation
% Max Value
x x
KPI_601 Balancing and maximization of power grid utilization
Avoidance of peaks and valley of energy consumption in the smart grid
100% x x x
KPI_602 Improvement of power grid stability
Average deviation of grid frequency and phase from normal operation and duration of power grid outages
% Min value x x
KPI_603 DER utilization Utilization of distributed energy resources 100% x x
Communication related KPIs
KPI_604 Availability of Service Availability of the Service, i.e. downtimes / failures 100% x x x x x
KPI_605 Successful transmissions of metering data
Ration of successful metering data transmissions to failed transmissions (i.e. necessary retransmissions)
100% x x x
KPI_606 Currentness of customer feedback system and metering data
Currentness of energy usage and tariff data displayed to the customer and metering data send to the HES
delta t Max Value x x x
KPI_607 Maintainability Ease of deploying Soft- and Hardware upgrades € & time Max Value x
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KPI_id KPI name Definition Goal WP2 WP3 WP4 WP5 WP6
Economical related KPIs
KPI_608 Amount of energy saved Energy saved per month kWh Max Value x x
KPI_609 Reduction of energy costs Energy costs saved per month € Max Value
KPI_610 Amount of acquired energy consumption data
Ratio of metered consumption to unmetered consumption 100%
KPI_611 Accuracy of energy tariff data
Deviation of customer energy tariffs and prices on the energy market
€ Min Value
KPI_612 Reduction of non-technical energy losses
Minimization of non-technical energy losses (i.e. illegal, unbilled energy consumption)
100% x x
Generic KPIs
KPI_613 User satisfaction with AMR / CEMS
General user satisfaction with AMR / CEMS functionality 100%
x
KPI_614 User satisfaction – Availability of Service
Served users / users requesting service 100% x x x x x
KPI_615 End-user usability Ease of use of the CEMS from an end-user perspective (for example through a user friendly interface)
Max. value
Table 12 Key Performance Indicators of the AMR / CEMS Use Case