Anti-electricity-stealing precise localization online monitoring method

Abstract

The invention discloses an anti-electricity-stealing precise localization online monitoring method. Models and anomaly screening rules about line loss anomaly indexes, electricity utilization anomaly indexes, metering device failure and anomaly alarming indexes, user historical business handling condition indexes, user historical electricity utilization service indexes and electricity price executing indexes are established through a known electricity stealing user electricity utilization data rule, a marketing business application system, an electric energy collecting system, a 95598 service complaint and customer basis file information are adopted as customer data sources, and suspected electricity stealing users are monitored in real time. Electricity utilization anomaly customers are investigated through an anti-electricity-stealing online monitoring platform, the loads, electricity quantity and other abnormal conditions of the customers are tracked in real time, the problem of difficult stealing investigation and evidence obtaining is fundamentally solved, anti-electricity-stealing working efficiency is effectively improved, and enterprise benefits are guaranteed.

Description

technical field [0001] The invention belongs to the field of electric power marketing inspection, and relates to an online monitoring method for anti-stealing and precise positioning. Background technique [0002] The conventional working mode of anti-theft electricity is to carry out periodic inspections to check theft. On the one hand, the number of personnel is limited and the strength is insufficient, so it is impossible to realize a comprehensive investigation of electricity customers. Even regional investigations also have low efficiency and time-consuming problems. Disadvantages are like finding a needle in a haystack, but the effect is unsatisfactory; on the other hand, the quality of the power inspection team is uneven, the success rate of on-site theft detection is low, the means of stealing electricity are insufficient, and there is no standardized technical guidance and data support for anti-theft work. , can only rely on experience; moreover, the methods of stea...

AI Technical Summary

Problems solved by technology

[0002] The conventional working mode of anti-theft electricity is to carry out periodic inspections to check theft. On the one hand, the number of personnel is limited and the strength is insufficient, so it is impossible to realize a comprehensive investigation of electricity customers. Even regional investigations also have low efficiency and time-consuming problems. Disadvantages are like finding a needle in a haystack, but the effect is unsatisfactory; on the other hand, the quality of the power inspection team is uneven, the success rate of on-site theft detection is low, the means of stealing electricity are insufficient, and there is no standardized technical guidance and data support for anti-theft work. , can only rely on experience; moreover, the methods of stealing electricity are becoming more and more subtle, and even steal electricity by using the principle of electric energy measurement. Usually, the time of stealing electricity cannot be accurately ascertained, and the amount of electricity stolen is also difficult to accurately determine. Therefore, in view of the above problems, The research applied a means of precise positioning and anti-stealing power based on big data analysis, established a normal online monitoring platform, made an anti-stealing monitoring data model, regularly carried out online centralized monitoring, accurately located suspected power-stealing households, and then obtained evidence through on-site Investigate and deal with electricity theft, solve the disorder of the needle-in-a-haystack inspection, and greatly improve the efficiency of anti-electricity theft. At the same time, the continuous online monitoring method has also achieved a breakthrough in the transformation of the anti-electricity theft work "from investigation to prevention"

Images