防窃电预警分析应用实施

pplication and implementation of early warning Analysis on electricity theft Prevention

基于电力用户用电信息采集系统的海量数据建立防窃电诊断分析模型,采用大数据挖掘和数据关联技术,实现对现场计量异常情况、窃电行为在线监测,支持动态产生异常事件告警,通过用户界面及时通知用户处理,方便灵活的开展防窃电分析业务。本文通过选取营销业务中的防窃电关键业务进行场景分析,获取业务系统提供的电能计量数据、各类事件记录、用户档案数据等,利用大数据的数据挖掘技术进行综合判断、分析,从而实现对计量异常情况、窃电行为的综合分析,达到窃电行为预警的目的,降低窃电行为分析的时间及成本。

Based on the massive data of electric power users＇ electric information collection system, a diagnosis and analysis model of anti-stealing electricity is established, and big data mining and data association technology are adopted to realize on-line monitoring of field metrological anomalies and electricity theft behavior It supports the dynamic occurrence of abnormal event alarm and notifies the user to deal with it in time through the user interface, which makes it convenient and flexible to carry out the anti-theft analysis service. In this paper, the key business of anti-stealing electricity in marketing business is selected for scene analysis, and the electric energy metering data, all kinds of event records and user file data provided by the business system are obtained, and the comprehensive judgment is made by using big data＇s data mining technology. Analysis to realize the measurement of In order to achieve the purpose of early warning of electricity theft, the time and cost of electricity theft analysis can be reduced by comprehensive analysis of electricity stealing behavior