1.State Grid Ningxia Electric Power Technical Research Institute,Ning Xia,Yin Chuan;2.State Grid Ningxia Electric Power Co,Ltd,Ning Xia,Yin Chuan
As a typical network model of artificial neural network, BP neural network has been widely used in fault diagnosis of distribution network. However, due to the randomness of initial weight and initial threshold, the diagnosis accuracy is not high in application. In this paper, a distribution network fault diagnosis method based on genetic algorithm optimization of BP neural network is proposed. The initial weight and threshold of BP neural network are optimized by genetic algorithm, and the fault diagnosis results are compared with those of traditional neural network in the calculation example. Finally, the simulation error values of the two are analyzed to verify the feasibility. The results show that the optimal initial weight and threshold of BP neural network can be obtained by using genetic algorithm, which can effectively reduce the error of operation results and make the diagnosis more accurate.