基于改进神经网络算法的互感器在线监测和故障诊断技术  

Transformer on-line monitoring and fault diagnosis technology based on improved neural network algorithm

作　　者：陈刚[1] 徐敏锐[1] 穆小星 郭云春 陈飞[1] Chen Gang;Xu Minrui;Mu Xiaoxing;Guo Yunchun;Chen Fei(Key Laboratory of Electric Energy Measurement of State Grid Corporation,Marketing Service Centerif State Grid Jiangsu Electric Power Co.,Ltd.,Nanjing 211103,China;Yangzhou Power Supply Branch of State Grid Jiangsu Electric Power Co.,Ltd.,Yangzhou 225000,Jiangsu,China)

机构地区：[1]国家电网公司电能计量重点实验室(国网江苏省电力有限公司营销服务中心),南京211103 [2]国网江苏省电力有限公司扬州供电分公司,江苏扬州225000

出　　处：《电测与仪表》2020年第11期49-54,62,共7页Electrical Measurement & Instrumentation

基　　金：国网公司科技项目(5210EF17001M)。

摘　　要：随着电网中电子式互感器广泛使用,互感器故障已成为亟待解决的问题。针对这一问题,设计了一种电子式互感器在线监测系统,对系统的组成和核心单元进行设计,结合BP神经网络和粒子群算法用于电子式互感器的故障诊断。并通过算例分析改进神经网络算法和BP神经网络算法的性能,结果表明,使用的诊断方法是有效地和可行的。所做研究工作为我国互感器线监测系统的发展提供了参考和借鉴。With the widespread use of electronic transformers in the power grid,the transformer faults have become an urgent problem to be solved.In view of this problem,this paper designs the online monitoring system of electronic transformer,designs the composition and core unit of the system,and applies BP neural network and particle swarm optimization to the fault diagnosis of electronic transformer.The advantages and disadvantages of the improved neural network algorithm and BP neural network algorithm are compared and analyzed by numerical examples,the results show that the fault diagnosis method adopted in this paper is effective and feasible.The research work provides a reference for the development of transformer online monitoring system in China.

关 键 词：电子式互感器 BP神经网络 粒子群 监测系统 故障诊断 

分 类 号：TM933[电气工程—电力电子与电力传动]