中国电机工程学报Issue(4)：562-569,8.DOI:10.13334/j.0258-8013.pcsee.2014.04.007
基于径向基函数神经网络和模糊积分融合的电网分区故障诊断
Divisional Fault Diagnosis of Power Grids Based on RBF Neural Network and Fuzzy Integral Fusion
摘要
Abstract
This paper presented an effective method for fault diagnosis of large-scale power grids based on radial basis function(RBF) neural network and fuzzy integral fusion. The study aims at effectively solving the diagnosis problem about the tie lines connecting regional sub-grids in the divisional fault diagnosis scheme. An overlapping network division method was proposed to divide a large-scale power grid into several sub-grids. When faults occur, regional RBF neural network diagnostic modules corresponding to different sub-grids are selectively triggered according to local alarm information which implies the faults exist in the sub-grids. Then faults of tie lines can be diagnosed by applying fuzzy integral to fuse the diagnostic outputs of two connected sub-grids about the tie lines. The method can not only be efficient in diagnosing the faults within local regions, but also in diagnosing the faults of tie lines well. The simulation results show that the proposed method is simple, efficient and can make up for the shortcoming of existing divisional fault diagnosis methods in diagnosis of tie lines. Moreover, it can diagnose different complex faults with good fault tolerance capability.关键词
大电网/电网分区/故障诊断/径向基函数神经网络/模糊积分Key words
large-scale power grid/grid division/fault diagnosis/radial basis function neural network/fuzzy integral分类
信息技术与安全科学引用本文复制引用
石东源,熊国江,陈金富,李银红..基于径向基函数神经网络和模糊积分融合的电网分区故障诊断[J].中国电机工程学报,2014,(4):562-569,8.基金项目
国家自然科学基金项目(50907024)。@@@@Project Supported by National Natural Science Foundation of China (50907024) （50907024）
