一种基于大数据的低压单相用户窃电分析方法

An Analysis Method of Low-Voltage Single-Phase Electricity Theft Based on Big Data

低压单相用户具有分布广、基数大的特点,随着人们用电量日益增大,低压单用户窃电现象越来越严重。目前窃电排查主要以人工逐户核查的方式为主,存在缺乏针对性、工作量大和效率低下等问题。文章提出了一种新型窃电分析方法,通过对用户电压、零火电流、电能表上报事件、台区等多维信息进行大数据分析,可有效、精准定位窃电用户,明确窃电手段。和传统人工排查方式对比,现场核查更具有针对性,大大缩小了现场核查范围,提高了工作效率和质量。

Low-voltage single-phase customers have the characteristics of wide distribution and large number.With the increasing power consumption,the phenomenon of electricity stealing by low-voltage single customers is becoming more and more serious.At present,the investigation of stealing electricity is mainly based on manual door-to-door verification,which has some problems such as lack of pertinence,heavy workload and low efficiency.In this paper,a new analysis method of electricity theft is proposed.By analyzing the multidimensional information such as customer voltage,zero fire current,electric energy meter reported events,distribution area,etc.,it can effectively and accurately locate the customers who steal electricity,and judge the means of electricity theft.Compared with the traditional manual investigation method,the on-site inspection is more targeted,which greatly reduces the scope of on-site inspection and improves the work efficiency and quality.