BIG DATA to Big INFORMATION Optimizing Transactive Controls in Hybrid Power Grids
Dr. Lawrence Jones
Vice President
Utility Innovations and Infrastructure Resilience
Alstom Grid Inc.
1
Panel: Using Smart Grid Data to Improve Planning, Analytics, and
Operation of the US Capital region T&D Systems
IEEE PES General Meeting
National Harbor, MD
July 29, 2014
“Big data refers to things one can do at a large scale that cannot be done at a smaller one, to extract new insights or create new forms of value, in
ways that change markets, organizations, the relationship betweencitizens and goverments and more .”
Big Data – A Revolution That Will Transform How We Live,
Work and Think. Viktor Mayer-Schonberger and Kenneth Cukier. 2013
What is Big Data?
Big Data is the Old, New and Future Normal
1 exabyte = 1, 000 000 000 000 000 000
Today we create approximately 5 exabytes every two days
Big Data Everywhere
Adapted from Big Data: The next Frontier for Innovation, Competition, and Productivity. Mckinsey Global Institute, May 2011
Internet of Things - Capacity
Devices connected to the Web:
• 1970 = 13
• 1980 = 188
• 1990 = 313,000
• 2000 = 93,000,000
• 2010 = 5,000,000,000
• 2020 = 31,000,000,000
Source: Intel; Adapted from Presentation by Chris Geer, NIST
Overview of the Electric System
More than 100 years Old – But Not Much has
Changed in the Physics . Not Until Now
Smarter Grids: when energy meets information…
Our New Hybrid Reality
“A permanently evolving electrical network, with a real-time, two-way flow of energy and
information, between power generation, grid operator, and end users. It is capable of
integrating all traditional and new players: renewable generation units (wind, solar, etc.),
electrical vehicles, electrical storage, or even entire smart cities”.
Smarter electricity systems (Source: IEA Smart Grid roadmap 2010)
Data determine the information which drives transactions
Field level PMU IED MeterDA DG CMU HANLine sensor
Others photos,videos,labs
analysis,site reports,Financial
Qty
TimeResolution
Type
1k 100k 10k 100k 10k 10M 100M10k
Weather
100k
1ms 100ms 10ms 1s 10min 1minto 15min
100M10k 100k
V I PhHz
V IHz
Sw MW MVA T°, Qual
MWhV I phHz
History
100M10k 100k
Files
100Tb
Comm(AMI, Tcom)
Signal Processing and Local Automation
GridOperations
BusinessOperations
CustomerEngagement
8
ScadaPDCMDM
Data to Information to @ to Wisdom
9
Relationships
Knowledge (How)
Patterns
Principles
HMI
Understanding (Why)
WisdomConnectedness
Data (Symbols)
Information (W,W,W)
Evaluated
"From Data to Wisdom", Journal of Applied Systems Analysis, Volume 16, 1989 p 3-9Graphic Original Illustration: Courtesy of Dr. Richard Candy, Eskom South Africa
Russell L. Ackoff
Value Creation and DeliveryMonetizing the Value of Control Actions
• Value of the grid services to end-users
• Value of the grid services to assets (e.g. DER, FACTS,
HVDC, microgrids)
• Value of assets to the grid
• Value of the grid to utilities
• Value of the grid to investors
• Value of the grid to society
We Use Controls - Signals and Actions - to Enhance
Performance Metrics and Maximize Value Across the Grid
• Efficiency
• Reliability
• Sustainability
• Flexibility
• Resilience
• Security
• Safety
Valuation of Responsive Distributed Energy Resource and Control Actions
Courtesy of Paul De Martini , Newport Consulting Group LLC
Determinants of Control Design and Optimization
Physics Operation
Economics /Markets
Information
Control
What is Transactive Energy/Control?
The technique for managing the generation, consumption or flow of electric power
within an electric power system through the use of economic or market based
constructs while considering grid reliability constraints – GWAC 1st Transactive Workshop
2012
“The term “transactive energy” is used here to refer to techniques for managing the
generation, consumption or flow of electric power within an electric power system
through the use of economic or market based constructs while considering grid
reliability constraints. The term “transactive” comes from considering that decisions
are made based on a value. These decisions may be analogous to or literally
economic transactions.” – recent IBM Workshop
“A set of economic and control mechanisms that allow the dynamic balance of
supply and demand across the entire electrical infrastructure using value as a key
operational parameter” - most recent GWAC discussion September 2013
“The ability to interact with every device that connects to the grid using price
signals as a basis for monetizing responses.” – NIST Smart Grid Advisory Committee Report
Transactive Control - Every Action Counts
What is it?
– Transactive control is a distributed method for coordinating responsive grid
assets wherever they may reside in the power system.
Incentive, feedback, and feed-forward signals
– The incentive signal sends a synthetic cost forecast to electricity assets
– The feedback signal sends a consumption pattern in response to the incentive.
Upstream
(toward generation, transmission,
distribution)
Downstream
(toward demand)
Incentive
Signal
Feedback
Signal
Modified
Feedback
Signal
Modified
Incentive
Signal
Source: Adapted from presentation by Dr. Ronald Melton, Pacific Northwest National Laboratory
BidsPrices
0 6 12 18 24
$/MWh
0 6 12 18 24
$/MWh
0 6 12 18 24
$/MWh
SG Value Signal
16
Two-Way, Hierarchical, Transactive Architecture Localizes and Balances Values & Prices
RTO Market / Production Costs$
MW
$
MW
MarketMarket
Generation Ops / RTO Market
OPF, LMPs / Transmission Ops
Distribution Ops
Energy Management Controls
InformationInfrastructure
billing impact
AMI
Information for each
layer of value signal
is entirely local
Honoring natural
domains keeps the
smart grid simple:
� protocols/standards are mostly quantity, cost, and time (“KISS”)
� honoring “need-to-know” enhances cyber
security transmission congestion
ancillary services
wholesale cost
Valuation
SG Value Signal
0 6 12 18 24
$/MWhdistribution
congestion
Transactive Control
Source: Presentation by Rob Pratt, PNNL
Transactive Controls � Flexibility
Existing and new flexibility needs can be met by a range of resources
in the electricity system – facilitated by power system markets,
operation and hardware.Source: Figure Adapted from Harnessing Variable Renewables, International Energy Agency
Enhanced T&D Grid Ops using DER Flexibility Services
Synchrophasors: The New Heartbeat of the Grid!Enabling Intelligent Decentralized Grid Monitoring & Control
EMS
Dynamic SecurityAssessment
State EstimationContingencyAnalysis
OfflineAnalysis
Modelling
Root CauseAnalysis
Wide AreaControls
Post-Event
Generator & ISOCompliance
New Smart GridApplications
Distribution
DMSDistributed Generation
DemandResponse
SynchroPhasors:‘the new heartbeat of the grid’
LocalControls
SynchrophasorAnalytics
µPMU Measurements Potential Applications
Source: “Every Moment Counts: Synchrophasor for Distribution Networks with Variable Resources” by A von Meier & Reza
Arghandeh. In Renewable Energy Integration ed. Lawrence Jones, Elsevier 2014.
Holistic Approach to Big Data AnalyticsA functional transverse layer that pulls data from all sources and generate value to each domain
2
1
Field level PMU IED MeterDA
PDC Scada
Comm
Field
gateways
Applications DMSEMSOSS
DG
CIS ERPGIS
Geo - Spatial
MMS
CMU
Telecom and AMR
ACM
UI Op Stations Mobile UI
DR Planning
HAN
DER
Meter DM
Customer Services
UtilityPerformance
GridOperations
Data Transform and Load
Data to InformationAdditional
Value to Users
Data Segmentation and Storage
UMDM is a facility to integrate real time data, meter data, financial data, and analyticsto bring value to Network Operations, Network Planning, Customer Services and Company Efficiency
UI Information
Presentation
GridAsset & Planning
HAN Mgr
Analytics
Containers
Collectors
UMDA
Others photos, videos, labs analysis, site reports @
Focus
Data
Data
Information
Transactive Controls and Predictive Analytics for
Managing Uncertainty in Hybrid Grids
Sec. Minutes Hours Days Months Years
To an
expanding
range of
scenarios
tomorrow.
Coping with Uncertainty• Increasing Variability• Data Uncertainty • Comprehension Uncertainty• Projection Uncertainty• Decision Uncertainty
Gazing ahead
today.
Predictive Operations Capability in Control Rooms
• Reduces the
impact of
variability and
uncertainty
on real-time
decision
making in the
control room
• Create new
value grid
services, e.g.
improve asset
utilization
Advanced Analytics for Big Information
Transition from Deterministic to Probabilistic Paradigms
Uncertainty Quantification
Including All Sources
Transmission
Tool
Better Utilization
of Transmission
Better/Modal
Control
Accurate
Security Margin
Quantification
Super Fast
Simulations
Understanding &
Prediction of
System Behavior
Deep Dive Tail
Event
Analysis
Simulation
of Blackouts
Probabilistic
Reliability Criteria
Stochastic Commitment
And Dispatch
Preventive
Redispatch
More Effective
Integration of
Renewables
Actionable
InformationData Driven
System Model
Predictive
Congestion
Source: “Incorporating Forecast Uncertainty in Utility Control Center” by Y. Markarov et..al. In Renewable Energy Integration
ed. Lawrence Jones, Elsevier 2014.
Conclusions
• Harness data and advanced analytics that produce
information to extract new insights, and create new value
streams.
• Use value-based controls for enhanced grid performance
and allocation of maximal benefits from services along
the electricity value chain.
