用电数据特征的窃电行为分析方法研究
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摘要
为提高反窃电效率,在用电信息采集系统的基础上提出一种窃电行为分析方法.即针对高供低计计量方式,建立窃电行为分析模型,并通过软件仿真验证模型的正确性.在此基础上,对各种窃电行为反映的负荷数据特征进行归纳总结,提出将实际窃电案例中可能遇到的窃电行为分成七类.通过负荷数据远程判断具体窃电行为类型,为现场稽查人员提供技术指导,从而提高窃电查证效率.
In order to improve the efficiency of anti-electric larceny,a kind of stealing behavior analysis method was put forward based on an electric energy data acquisition system.Several models of stealing behavior were established for high voltage side power supplying and low voltage side metering and the correct of model was verified by software simulation.The characteristics of the load data reflected by various kinds of stealing behavior were then summarized.It was proposed to divide the stealing behavior which might be encountered in the actual stealing cases into seven categories.Analyzing on the remote load data can determine the specific behavior types of theft and provide technical guidance for on-site inspectors.Therefore,the verification efficiency of electricity theft is improved.
In order to improve the efficiency of anti-electric larceny,a kind of stealing behavior analysis method was put forward based on an electric energy data acquisition system.Several models of stealing behavior were established for high voltage side power supplying and low voltage side metering and the correct of model was verified by software simulation.The characteristics of the load data reflected by various kinds of stealing behavior were then summarized.It was proposed to divide the stealing behavior which might be encountered in the actual stealing cases into seven categories.Analyzing on the remote load data can determine the specific behavior types of theft and provide technical guidance for on-site inspectors.Therefore,the verification efficiency of electricity theft is improved.
引文
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[3]肖坚红,严小文,周永真,等.基于数据挖掘的计量装置在线监测与智能诊断系统的设计与实现[J].电测与仪表,2014,51(14):1-5.XIAO J H,YAN X W,ZHOU Y Z,et al.Design and implementation of metering device online monitoring and intelligent diagnosis system based on data mining[J].Electrical Measurement and Instrumentation,2014,51(14):1-5.
[4]王珏昕,孟宇,殷树刚,等.用电信息采集系统反窃电功能现状及发展趋势[J].电网技术,2008,32(增刊2):177-178.WANG J X,MENG Y,YIN S G,et al.The present situation and development trend of anti electric stolen function of power demand information acquisition system[J].Power System Technology,2008,32(Suppl 2):177-178.
[5]王颖琛,顾洁,金之俭.基于高维随机矩阵分析的窃电识别方法[J].现代电力,2017,34(6):71-78.WANH Y C,GU J,JIN Z J.Electric larceny recognition method based on high dimensional random matrix analysis[J].Modern Electric Power,2017,34(6):71-78.
[6]NAGI J,YAP K S,TIONG S K,et al.Nontechnical loss detection for metered customers in power utility using support vector machines[J].IEEE Transactions on Power Delivery,2010,25(2):1162-1171.
[7]ANGELOS E W S,SAAVEDRA O R,CORTéS O A C,et al.Detection and identification of abnormalities in customer consumptions in power distribution systems[J].IEEE Transactions on Power Delivery,2011,26(4):2436-2442.
[8]饶艳文,范杏元.高压供电计量方式的选择[J].电测与仪表,2012,49(10A):80-83.RAO Y W,FAN X Y.The selection of high-voltage power supply metering methods[J].Electrical Measurement and Instrumentation,2012,49(10A):80-83.
[9]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,2010,46(5):86-88.GUO L C,PENG Z W,FAN Q.A survey of electric energy metering and countermeasures to electric power stealing[J].High Voltage Apparatus,2010,46(5):86-88.
[10]高明,史涛,叶生,等.浅谈窃电技术与反窃电措施[J].电气应用,2015,34(增刊1):122-124,128.GAO M,SHI T,YE S,et al.Discussion on electricity theft and anti-electricity larceny measures[J].Electrotechnical Application,2015,34(Suppl 1):122-124,128.