Assessing Power System Resilience to Adverse …...In order to quantify the changes in system...
Transcript of Assessing Power System Resilience to Adverse …...In order to quantify the changes in system...
Sandia National Laboratories is a multi-mission laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL85000. SAND NO. 2011-XXXXP
AssessingPowerSystemResiliencetoAdverseWeatherEvents
AndreaStaidINFORMSComputingSocietyConference
January17,2017
WhatisInfrastructureResilience?
Definitions:§ Theabilitytoprepareforandadapttochangingconditionsand
withstandandrecoverrapidlyfromdisruptions.– PresidentialPolicyDirective21§ Theabilitytoreducethemagnitudeand/ordurationofdisruptive
events.– NationalInfrastructureAdvisoryCouncil§ Anticipate– Identifyandplanforadverseevents(deliberateattacks,accidents,
ornaturaldisasters)§ Absorb– Continueoperatingaftershockstosystem§ Adapt– Adjustsysteminrealtimetominimizeadverseimpacts§ Recover– Returnsystemoperationstonormalstateasfastaspossible
Howisitdifferentfromreliability?§ Resilience focusesonlow-probability,high-consequenceevents§ Reliability focusesonhigh-probability,low-consequenceevents
§ Day-to-Dayoperations2
Howtoimproveresilience?
§ Mustbeabletomeasureit!§ Usearisk-basedapproach
§ Identifythreatsofconcern§ Resilienttowhat?Improvementsmustbetargetedataspecifictypeofthreat.
§ Increasedresilienceagainsthurricanesmaynothelpwithresiliencetoterrorattacks.Approachisgenerallythreat-specific.
§ Assesslikelihoodofsystemdisruptiongivenathreat§ Evaluateconsequencesofdisruption
§ Moreresilientsystemswillminimizelikelihoodofdisruption,severityofconsequences,orboth
§ Needaquantifiablemetricgivenaspecificthreat
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ResiliencyAnalysisProcess
§ Frameworkforquantificationofpowersystemresilience§ Thisframeworkenablesdecisionmakingtoobtain
demonstrableresilienceimprovements
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Prob
abilit
y of
Con
sequ
ence
s [$
] G
iven
Thr
eat X
Consequences [$]
Reduced Expected Financial Consequence
Reduced Risk
Baseline System Resilience
Resilience of System after Improvements Improvements must
cost significantly less than E-E’
E’(C) E(C)
§ Resultingresiliencemetricsareprobabilistic
§ Theframeworkisflexible:§ Canhandledifferenttypes
ofthreats§ Providesinformationfor
differenttypesofdecisionmakers
ResilienceFramework
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Define Resilience
Goals
Define System & Resilience
Metrics
CharacterizeThreats
Determine Level of Disruption
Define & Apply System Models
Calculate Consequence
Evaluate Resilience
Improvements
Populate
Define Resilience
Goals
Define System & Resilience
Metrics
CharacterizeThreats
Determine Level
of Disruption
Define & Apply System Models
Calculate Consequence
Evaluate Resilience
Improvements
Create
ScenarioAnalysis:IdentifyThreats
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§ Whatisthepossiblethreatspace?
§ Consequences(andprotectivemeasures)canvarydrasticallyamongthreats.
§ Focusonimprovingsystemresilienceagainstanindividualthreat.
ScenarioAnalysis:CharacterizeIndividualThreat
§ Givenhigh-levelthreatcharacterization,thenextstepistofurtherrefinethedescriptionofthespecificthreats
… …
Historicalinformationandforecastmodelsusedtoguidespecificationofpossibleeventsandtheirrelativelikelihoods
p1 p2 pn
Category4,north-of-peninsulastormtrack
Category5,eyetracksovermetropolitanarea
Category2,landfallathightide
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ScenarioAnalysis:DisruptingtheSystem
… …p1 p2 pn
Category4,north-of-peninsulastormtrack
Category5,eyetracksovermetropolitanarea
Category2,landfallathightide
……
Givenaspecificmanifestationofadisruptionevent,wethenspecifyadistribution ofinfrastructureimpacts
DamageRealizationN
DamageRealizationK
Assumeuniformprobabilities
Forexample:1. Normaldistributionofgeneratorfailures,
withu=20,s=52. Normaldistributionoflinefailures,with
u=40,s=7
§ Thefinalstepistotranslatedisruptioneventsintosystemimpacts
CaseStudy– AEPAdverseWeather
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§ AmericanElectricPower(AEP)isalargeelectricutilityintheU.S.§ Serving5.4millioncustomersin11states§ OwnslargesttransmissionnetworkintheU.S.– Morethan40,000
miles– and31GWofgeneratingcapacity
§ Interestedinimprovingresiliencytoadverseweathereventsintheir‘East’territory
ImprovementOptions
§ Transmissionsystemresiliencycanbeimprovedby:§ Hardeninglines
§ Reducinglikelihoodoffailureforindividuallines§ Long-termplanningdecision
§ Generatorre-dispatchand/ortransmissionswitching§ Inadvanceofastorm,re-dispatchsystemtomaintainpowertocustomers
§ Real-timedecisionswhenadverseweatherinforecast
§ Demonstratebenefitofpossibleactionusingscenariosofweatherevents§ Compareproactivedecisionsto‘businessasusual’case
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AnalyzingSystemResponse
§ Wouldtherebeabenefittore-dispatchingthesysteminadvanceofastorm?Canthisincreaseresilience?
§ Usehistoricalstormstobuildscenariosofrealisticfuturestorms§ Futurestormsunlikelytoexactlymirrorpaststorms,butsystem
weaknessescanbecaptured§ Historicalprobabilityofoutagevariesdrasticallyacrosslines
§ Scenariogenerationforthreeapplicationareas:§ Identifycandidatesforlinehardening§ Demonstratevalueofreal-timegeneratorre-dispatch§ Developtoolforreal-timeuseinadvanceofoncomingweather
§ Inwork
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Number of Outages per Circuit
Density
0 20 40 60 80 100
0.00
0.02
0.04
0.06
0.08
0.10
Number of Outages per Event (Log Scale)
Density
0 1 2 3 4 5
0.0
0.2
0.4
0.6
0.8
1.0
AvailableData§ Transmissioncircuitoutagedatafrom~1990– 2015§ Mostcircuits seeveryfewoutages,butsomehavemany§ Moststorms causeveryfewoutages,butsomestormsresultin
hugenumbers(e.g.,June2012Derecho,SuperstormSandy)
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ScenarioGeneration
§ Needtorepresentspectrumofstormdamage:§ Randomsamplingfor‘standard’scenarios§ Augmentedsamplingfor‘worstcase’scenarios
§ Forcelargernumberofoutages(uptoselectedmaximum),stillusingbaselineprobabilitiestosample
§ Complications:§ Probabilitiesoflineoutagescanbeconditionalontypeofweather
§ But,realdataismessy,mostoftheoutagecause-codescannotbetrusted§ Somestormeventshavespatiallydistributedoutages,othersvery
concentrated§ Needto‘force’scenariostorepresentbothtypes.Don’tyethaveenoughdatatodothiswell
§ Outagesmustrepresentcascadingfailuresinsystem§ Linkscenariosto‘contingency’dataonpropagatingfailures§ Givesrealisticrepresentationofhowsystemwouldhandleanoutage 13
AnticipativeOperations§ StochasticOptimizationallowingforanticipativeoperations
§ Basedonuncertainscenariosofadverseweatherimpact,howbesttore-dispatchgeneratorstominimizelossofload?
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BASELINE RE-DISPATCH
NextSteps– Real-TimeTool
§ Createscenariosforuseinreal-timedecisionsasstormapproaches
§ Linkweatherdatatoprobabilityofoutage;Circuitoutagewillbeafunctionof:§ Windspeed,Precipitation,Temperature,Lightningforecast,etc.
§ Generatescenariosbasedonuncertaintyinweatherforecast,stormtrack,andprobabilityoffailure
§ Simulatesuggesteddecisionsforre-dispatchonAEPsystemforactualweatherevents
§ Quantifychangeinconsequences(lossofload)acrosssystem
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SomeFinalThoughts
§ Demonstratedbenefittosystemoperatorsbybeingproactivewhenitcomestoweather
§ Inordertoquantifythechangesinsystemresiliencetoadverseweather,wechosetodevelopscenariosof‘stormevents’representedbytransmissionlinefailures
§ Workingtowardsareal-timetool;movesfromtheoreticallyimprovingresiliencetoofferingsuggestedactionstominimizelossofload§ Highlydata-dependent,shouldbeexciting!
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Questions?
Contact:[email protected]
Acknowledgements:AmericanElectricPowerforprovidingthedataDHSandDOE/EPSAforfunding
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