【配电网非技术损失检测方法研究的国内外文献综述3300字】

–[28]。基于以上研究，传统的检测方法具有很多弊端，如耗费大量人力物力、检测时间长、直接检测困难、专业人员不足等问题；对于基于数据挖掘的检测方法，利用经典的机器学习算法进行建模，但是其检测精度有待提高。对此，本文拟用深度学习算法，用于配电网非技术损失的检测。参考文献Z.Markoc,N.Hlupic,D.Basch.Detectionofsuspiciouspatternsofenergyconsumptionusingneuralnetworktrainedbygeneratedsamples[J].ProceedingsoftheITI2011,33rdInternationalConferenceonInformationTechnologyInterfaces,2011:551-56.李宁,尹小明,丁学峰,等.一种融合聚类和异常点检测算法的窃电辨识方法[J].电测与仪表,2018,55(21):19-24.P.Mcdaniel,S.Mclaughlin.SecurityandPrivacyChallengesintheSmartGrid[J].IEEESecurity&Privacy,2009,7(3):75-77.G.M.Messinis,A.E.Rigas,N.D.Hatziargyriou.AHybridMethodforNon-TechnicalLossDetectioninSmartDistributionGrids[J].IEEETransactionsonSmartGrid,2019:1-1.S.S.S.R.Depuru,L.F.Wang,V.Devabhaktuni.Electricitytheft:Overview,issues,preventionandasmartmeterbasedapproachtocontroltheft[J].EnergyPolicy,2011,39(2):1007–1015.陈启鑫,郑可迪,康重庆,等.异常用电的检测方法:评述与展望[J].电力系统自动化,2018,(17):189-199.钟立华,杨悦群.用电监察中窃电与反窃电技术分析[J].电子测试,2018(21):117-118.宋亚奇,周国亮,朱永利.智能电网大数据处理技术现状与挑战[J].电网技术,2013,37(04):927-935.A.Labrinidis,H.V.Jagadish.Challengesandopportunitieswithbigdata[J].ProceedingsoftheVLDBEndowment,2012,5(12):2032–2033.P.Glauner,J.A.Meira,P.ValtchevP,etal.TheChallengeofNon-TechnicalLossDetectionusingArtificialIntelligence:ASurvey[J].InternationalJournalofComputationalIntelligenceSystems,2017,10(1):760-775.霍尧.基于用电信息采集的智能反窃电系统开发与应用[D].华北电力大学,2014.郭立才,彭志炜,范强.电能计量及反窃电方法综述[J].高压电器,2010(05):91-93+96.刘崇伟,李韵.智能电能表防窃电技术研究[J].电气应用,2014(1):82-85.J.Nagi,K.S.Yap,S.K.Ahmed,etal.NontechnicalLossDetectionforMeteredCustomersinPowerUtilityUsingSupportVectorMachines[J].IEEETransactionsonPowerDelivery,2010,25(2):1162-1171.D.R.Pereira,M.A.Pazoyi,L.A.M.Pereira,etal.Social-SpiderOptimization-basedSupportVectorMachinesappliedforenergytheftdetection-ScienceDirect[J].Computers&ElectricalEngineering,2016,49:25-38.宋南.基于电能信息的电表现场校验状态分析研究[D].浙江大学,2011.I.Monedero,F.Biscarri,C.Leon,etal.Detectionoffraudsandothernon-technicallossesinapowerutilityusingPearsoncoefficient,Bayesiannetworksanddecisiontrees[J].InternationalJournalofElectricalPower&EnergySystems,2012,34(1):90-98.C.Ramos,A.N.DeSousa,J.P.Papa,etal.ANewApproachforNontechnicalLossesDetectionBasedonOptimum-PathForest[J].PowerSystems,IEEETransactionson,2011,26(1):181-189.V.Ford,A.Siraj,W.Eberle.Smartgridenergyfrauddetectionusingartificialneuralnetworks[C]2014IEEESymposiumonComputationalIntelligenceApplicationsinSmartGrid(CIASG).IEEE,2015,1-6.E.Manitsas,R.Singh,B.C.Pal,etal.DistributionSystemStateEst