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1、1542IEEETRANSACTIONSONPOWERSYSTEMS,VOL.25,NO.3,AUGUST2010NovelDynamicRepresentationandControlofPowerSystemsWithFACTSDevicesShahabMehraeen,StudentMember,IEEE,S.Jagannathan,SeniorMember,IEEE,andMariesaL.Crow,Fellow,IEEEAbstract—FACTSdeviceshavebeenshowntobeusefulinSeveralapproacheshavebeenanalyzed
2、forsystemwidedampingpowersystemoscillations.However,inlargepowersys-FACTScontroldesign.Pastwork[2]–[6]hasproposedtolin-tems,theFACTScontroldesigniscomplexduetothecombinationearizethedifferential-algebraicequationnetworkandeliminateofdifferentialandalgebraicequationsrequiredtomodelthethealgebraic
3、equationsthroughreductionmethods.Then,linearpowersystem.Inthispaper,anewmethodtogenerateanonlineardynamicrepresentationofthepowernetworkisintroducedtocontrolmethodsareappliedtothelinearizedpowersystem.enablemoresophisticatedcontroldesign.Oncethenewrepresen-Thisapproach,however,tacitlyassumesthat
4、thenetworktationisobtained,abacksteppingmethodologyfortheUPFCisvariablesremainintheneighborhoodofthedesiredoperatingutilizedtomitigatethegeneratoroscillations.Finally,theneuralpoint.Inaddition,theplacementandnumberofUPFCde-networkapproximationpropertyisutilizedtorelaxtheneedforvicesaredetermined
5、heuristically.Bycontrast,in[7]–[12]aknowledgeofthepowersystemtopologyandtoapproximatethenonlinearuncertainties.Thenetresultisapowersystemsingle-machineinfinitebusmodelisusedtoapplynonlinearrepresentationthatcanbeusedforthedesignofanenhancedcontrolschemes.However,theinfinitebusassumptionrequiredFAC
6、TScontrolscheme.Simulationresultsaregiventovalidateforthisapproachisnotvalidforlargemulti-machinesystemsthetheoreticalconjectures.whenthefaultaffectsthepowersystem.IndexTerms—FACTS,neuralnetworks,nonlinearsystems,FACTSdeviceshavebeenconsideredin[13]–[16]viauti-powersystemcontrol.lizingenergyfunc
7、tionstodevelopthecontrollersandestimatethecriticalclearingtime.Thisapproachisnotpracticalforcon-trollerdevelopmentbecauseitrequiresthecalculationoftheI.INTRODUCTIONderivativesofpowersystembusvoltagesandanglesandre-quiresnume
