基于GA-BP神经网络的反窃电系统研究与应用

王庆宁

王庆宁.基于GA-BP神经网络的反窃电系统研究与应用[J].电测与仪表,2018,55(11):35-40.
wangqingning.Research and Application of Electricity Anti-stealing System Based on BP Neural Network[J].Electrical Measurement & Instrumentation,2018,55(11):35-40.

基于GA-BP神经网络的反窃电系统研究与应用

Research and Application of Electricity Anti-stealing System Based on BP Neural Network

DOI：

中文关键词: 窃电指标评价体系 BP神经网络用户信用等级评价

英文关键词:indictor evaluation system electricity anti-stealing model BP neural network credit rating

基金项目:

作者中文名	作者英文名	单位
王庆宁	wangqingning	武汉理工大学

摘要点击次数: 2042

中文摘要:

针对目前电力行业在用电自动化管理相对落后的问题，本文基于BP神经网络算法构建了一种差异化的反窃电数学模型。首先综合多种因素建立用电系统指标评价体系，利用数据挖掘技术对电力用户积累的海量用电数据进行处理，通过BP神经网络建立电力企业用电行为分析的数学模型，从而可以得到用户的窃电嫌疑因子以及窃电方式，从而实现用户的用电状态信用等级评价。选取相关企业进行验证，证明本文建立的反窃电模型针对窃电问题提供了一种切实可行的方案。

英文摘要:

Nowadays, the backwardness of the power automation management in our country causes the loss of a lot of energy. In order to improve the situation, an anti-stealing mathematical model is introduced in this paper. Firstly, ten factors are selected to build the indictor evaluation system, data mining is used to process lots of the electricity data. Then, a mathematical model based on BP neural network is built for analyzing the customer consumption behavior. With the model, the suspicion coefficient of electricity stealing can be calculated, and the credit rating of power consumer is also classified. In this paper, some typical companies are selected to verify the electricity anti-stealing model, and come to a conclusion that it provides a feasible idea for the electricity stealing problem.

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