首页 | 本学科首页   官方微博 | 高级检索  
     

自适应的窃漏电诊断方法研究及应用
引用本文:刘涛,杨劲锋,阙华坤,肖勇.自适应的窃漏电诊断方法研究及应用[J].电气自动化,2014(2):60-62.
作者姓名:刘涛  杨劲锋  阙华坤  肖勇
作者单位:[1]广东电网公司电力科学研究院,广东 广州510080 [2]华南理工大学 电力学院,广东 广州510641
基金项目::广东电网公司重点科技项目,K-GD2012-341,大规模智能用电系统海量数据处理与数据挖掘技术研究及应用
摘    要:基于已有电能计量自动化系统的实时采集的电量、负荷、报警及线损数据,分析现有用电检查所得窃电现象的样本,通过构建指标体系,建立一种自适应的防窃漏电诊断模型。基于模糊评价法与神经网络方法,结合了两者的优点,能够反映窃漏电现象的特征。经实证研究,能够实时监测计量自动化系统的运行数据,发现诊断窃漏电现象,具有较强的识别能力。

关 键 词:窃漏电  计量自动化  模糊神经网络  自适应  负荷梯度

Study and Application of a Self-adaptive D iagnosis Method for Electricity Stealing and Leakage
LIU Tao,YANG Jin-feng,QUE Hua-kun,XIAO Yong.Study and Application of a Self-adaptive D iagnosis Method for Electricity Stealing and Leakage[J].Electrical Automation,2014(2):60-62.
Authors:LIU Tao  YANG Jin-feng  QUE Hua-kun  XIAO Yong
Affiliation:1. Electric Power Research Institute of Guangdong Power Grid Corporation, Guangzhou Guangdong 510080, China; College of Electric Power, South China University of Technology, Guangzhou Guangdong 510641, China)
Abstract:Based on the data collected on a real-time basis by the existing automatic electric power metering system about quantity of electricity, load,alarm and line loss,this paper analyzes electricity stealing samples obtained in the current inspection method,and by creating an index system,establishes a self-adaptive diagnosis model for electricity stealing and leakage.Combining fuzzy evaluation method and neural network method,this model can monitor on a real-time basis the operational data of the automatic metering system to detect electricity stealing and leakage and has a strong capability of identification.
Keywords:electricity stealing and leakage  automatic metering  fuzzy neural network  self adaptation  load gradient
本文献已被 CNKI 维普 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号