DocumentCode
1774144
Title
Fault location in distribution network with distributed generation based on neural network
Author
Ge Liang ; Peng Liyuan ; Liu Ruihuan ; Zhou Fen ; Wang Xin
Author_Institution
Beijing Sifang Autom. Co., Ltd., Beijing, China
fYear
2014
fDate
23-26 Sept. 2014
Firstpage
209
Lastpage
212
Abstract
In this paper, the fault location problem of the distribution network with distributed generations(DGs) is studied. A fault identification and location method based on multi-stage neural network is proposed. Particle Swarm Optimization (PSO) algorithm is employed to optimize the network structure. The model and algorithm realize the fault location accurately. And when the input variables increases, When the input variables increases, its size is much reduced through gradual decomposition of the network compared to traditional the single-stage network. Finally, a typical distribution network with distributed generation is established in the Digsilent environment. The sample data are obtained through simulation experiment. The neural network model is established in Matlab to get the algorithm results. The experiment verified the correctness and effectiveness of the model and algorithm.
Keywords
distributed power generation; fault location; neural nets; particle swarm optimisation; power distribution faults; power engineering computing; Digsilent environment; Matlab; PSO algorithm; distributed generation; distribution network; fault location method; fault location problem; gradual decomposition; multistage neural network; neural network model; particle swarm optimization; single-stage network; Abstracts; Artificial neural networks; Fault location; Distributed Generation (DG); Fault Location; Multi-Stage Neural Network; Particle Swarm Optimization (PSO);
fLanguage
English
Publisher
ieee
Conference_Titel
Electricity Distribution (CICED), 2014 China International Conference on
Conference_Location
Shenzhen
Type
conf
DOI
10.1109/CICED.2014.6991695
Filename
6991695
Link To Document