Post on 03-Feb-2022
transcript
IRRIIS
Increase of power system survivability:Decision Support Tool “CRIPS”based on Network Planning
IRRIIS - FP6-2005–IST-4
EC - LOGO
Christine SchwaegerlOlaf Seifert
Robert BuschmannHermann DellwingStefan GeretshuberClaus Leick
IRRIIS
Decision-Support Tools for the Power Domain
1. Most approaches use a physical model of the system (online simulation)
2. Other approaches use data-mining techniques, when the underlying problem needs accurate classification or detection of patterns
3. Our approach presented here is to formalize and capture the human expert knowledge and then build a tool based on “expert-system” techniques (rule-based systems)
What we mean is a tool which can provide suggested (control) actions (to the operator)
IRRIIS
The Decision-Support Tool “CRIPS”
Acronym: Crisis Planning and Prevention SystemCRIPS is a Knowledge Based Expert SystemCRIPS is one of the “MIT add-on Components”developed within the IRRIIS ProjectCRIPS supports Operators by– Assessing of the current situation based on
dependency structuresinsights gained during exercises = Expert Knowledgeexperiences from incidents
– Suggesting Actions/Decisions based on this assessment
IRRIIS
command
archive & visualise
monitor&
collect data
controladjust & optimise
Tasks of a Power System Operator
Measurement of Operator’s UtilisationMeasurement of Operator’s Utilisation
Operator
IRRIIS
Time
Network in Secure Operation
Source: IRRIIS deliverable D 3.3.2
Triggering Event
Network in Disturbed Operation
Wrong Decision by Operator Right Decision by Operator
Cascading Triggering of Protection Devices
Point of no Return
Additional Failure
Action by Operator
Additional FailureAdditional Failure
Blackout
Emergence of a Power Blackout
Rec
over
y
IRRIIS
Time
Network in Secure Operation
Triggering Event
Network in Disturbed Operation
Cascading Triggering of Protection Devices
Point of no Return
Action by Operator
Blackout
Reaction Times
Minutes to Hours
Milliseconds toSeconds
Decision Support
IRRIIS
ES
ETRM
SA
PAITS
DTSTNA
UIDW
HFDFA
Tools
SDMBS
FISR
DNAOMS
VVCCMS
OFRNTLO
TCS
SCADA
CAMSCFE
SCADA
Trading
Generation
Transmission
DistributionET Energy Trading RM Risk Management ES Energy Sales, Customer Management
ITS Interchange Transaction
SA Scheduling Applications
PA Power Applications
TNA Transmission Network Applications
DTS Dispatcher Training Simulator
CFE Communication Front-EndCA Communication AppsSCADA Supervisory ControlMS Multi-site
BS Base SystemSDM Source Data ManagementUI User InterfaceDW Data WarehouseHFD Historical and Future Data FA Forecast Applications
DNA Distribution Network ApplicationVVC Volt/Var ControlFISR Fault Isolation/System RestorationOMS Outage ManagementCMS Crew Management SystemTCS Trouble Call SystemOFR Optimal Feeder ReconfigurationNTLO Non-Technical Losses
Input for Power System Operator
IRRIIS
Power System Operator Behaviour
Operator
ES
ET
RM
SA
PA
ITS
DTS
TNA
UI
DW
HFD
FA
Tools
SDM
BS
FISR
DNA
OMS
VVC
CMS
OFR
NTLO
TCS
SCADA
CA
MSCFE
IT-Systems
Environmental Conditions
Historical Incidents
Guidelines
Law
s
Grid
Cod
e
Con
tinge
ncy
Plan
Ope
ratio
nal
Han
dboo
ks
GeographicRealities
Decisions
Potential Input for Rules
IRRIIS
1. Develop a Scenario (Topology)
2. Build a Simulation Model
3. Acquire “Expert Knowledge“
4. Formalise & Model Knowledge
5. Validate Approach
Knowledge Engineering Processin the IRRIIS Project
KnowledgeEngineer
HumanExpert
KnowledgeBase of
Expert System
Dialog
Explicit
CRIPS
IRRIIS
CRIPS – Expert System
CRIPS
SCADA
Expert
Expert Knowledge
Present Situation
Rules SituationAssessment
Decision SupportFacts
one-time
continuously Operator
IRRIIS
Conclusions
The weakest part of the control chain is the human operatorAdvanced technology is taking load from the operatorNot every problem can be described by physicsSo an expert system can support decision and strategic assessmentSpecific suggestions still have to be validated by online simulationVery good relationship “simplicity – efficiency”