Journal of Jishou University(Natural Sciences Edition)

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Distribution Network Fault Diagnosis Based on Improved RBF Neural Network

WEI Jianbo,ZHANG Dongzhu,LUO Haojie,TAN Hui,WEI Tao   

  1. (1.Hechi Power Supply Bureau,Guangxi Power Grid Company,Hechi 547000,Guangxi  China;2.Hunan Yingke Electric Power Technology Co. Ltd.,Changsha 410000,China)
  • Online:2018-01-25 Published:2018-01-27


RBF neural network is effective for nonlinear fault diagnosis,but such method has the problem of local minimum and slow convergence.Evolutionary algorithm has strong global search ability,and it can realize parameter optimization for the RBF neural network through intersection,selection and aberrance;but during parameter optimization,covergence is slow.This paper proposes a distribution network fault diagnosis model based on improved RBF nueral network through combination of gradient descent algorithm and evolutionary numerical hybrid method.Application expriments show that this model has a high diagnostic accuracy.

Key words: RBF neural network, improvement, distribution network, fault diagnosis

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