摘要
反窃电作为供电企业用电管理工作的核心构成部分,在剖析和处置用户窃电行为数据的基础上,研究出一种基于用电特点剖析的窃电行为鉴别手段,能明显提升搜集数据的合理性。本文主要围绕窃电行为识别方法的总体设计构思展开分析,通过用户用电量多指标综合评分等手段,利用大数据算法对目标用户的用电行为特征加以分析,在此基础上建立相应的特征模型,创新提出了基于用户行为特征大数据的用电异常识别技术路线,并探究其具体建设过程,旨在提高供电水平,促进企业可持续发展。
The acquired data of users’ electricity stealing behavior should be reasonably analyzed and processed. As the core component of power use management in power supply enterprises, anti stealing is based on the analysis and disposal of users’ electricity stealing behavior data, and a method to identify electricity stealing behavior based on the analysis of electricity use characteristics is developed, which can significantly improve the rationality of data collection. This paper will mainly focus on the overall design concept of the identification method of electricity theft behavior. This paper analyzes the characteristics of the target users’ electricity use behavior by using big data algorithm through the means of multi index comprehensive scoring of users’ electricity consumption, and on this basis, establishes the corresponding feature model, innovatively proposes the technical route of identification of suspected users of abnormal electricity use based on the big data of users’ behavior characteristics, and explores its specific construction process, It aims to improve the power supply level and promote the sustainable development of enterprises.
作者
万龙
黄河滔
张兴霖
WAN Long;HUANG Hetao;ZHANG Xinglin(Zhaotong Power Supply Bureau of Yunnan Power Grid Co.,Ltd.,Yunnan Zhaotong 657100,China)
出处
《电工材料》
CAS
2023年第1期64-67,共4页
Electrical Engineering Materials
关键词
用电特征
大数据
行为识别
用电异常
power consumption characteristics
big data
Behavior recognition
Abnormal power consumption
