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1、IEEETRANSACTIONSONSMARTGRID,VOL.5,NO.1,JANUARY2014431AnalysisofConservationVoltageReductionEffectsBasedonMultistageSVRandStochasticProcessZhaoyuWang,StudentMember,IEEE,MiroslavBegovic,Fellow,IEEE,andJianhuiWang,SeniorMember,IEEEAbstract—Thispaperaimstodevelopanovelmethodtoe
2、val-ActiveloadattimeonthetestdayuateConservationVoltageReduction(CVR)effects.AmultistageSupportVectorRegression(MSVR)-basedmodelisproposedtoes-Activeloadattimeonthekthnon-testdaytimatetheloadwithoutvoltagereductionduringtheCVRperiod.The?rststageistoselectasetofloadpro?lesth
3、atareclosetotheNumberofdatapointsduring(pre-CVR)andpro?leunderestimationbyaEuclidiandistance-basedindex;the(post-CVR)periodssecondstageistotraintheSVRpredictionmodelusingthepre-se-lectedpro?les;thethirdstageistore-selecttheestimatedpro?lestoEuclidiandistance-basedvoltageind
4、exforkthminimizetheimpactsofestimationerrorsonCVRfactorcalcula-non-testdaytion.ComparedwithpreviouseffortstoanalyzetheCVRoutcome,thisMSVR-basedtechniquedoesnotdependonselectionsofcon-VoltageattimeonthetestdaytrolgroupsorassumptionsofanylinearrelationshipbetweentheVoltageatt
5、imeonthekthnon-testdayloadanditsimpactfactors.InordertodealwiththevariabilityofCVRperformances,astochasticframeworkisproposedtoassistThresholdvalueofandutilitiesinselectingtargetfeeders.TheproposedmethodhasbeenappliedtoevaluateCVReffectsofpracticalvoltagereductiontestsNumbe
6、rofnearestpro?lesselectedbyEuclidianandshowntobeaccurateandeffective.distance-basedindexesIndexTerms—Conservationvoltagereduction(CVR),EuclidianLoadconsumptionondaydistance,short-termloadforecasting,Kolmogorov-Smirnov(K-S)test,supportvectorregression(SVR).Nonlinearrelations
7、hipbetweenloadconsumptionanditsimpactfactorsI.NOMENCLATURETemperaturepro?leondayActiveloadconsumptionwithCVRHumiditypro?leondayActiveloadconsumptionwithoutCVREstimatedparametersofMLRReducedvoltagelevelEstimatedCVRfactorNormalvoltagelevelActualCVRfactorActiveloadconsumptionb
8、eforeCVRtestActualdataActiveloadconsumptionduringCVRperiodForecasteddataActiveload
