Research on Fault Line Detection for Distribution Network based on Improved PSO to Optimize Fuzzy Neural Network
Wang Lei1, 2, Cao Xianfeng1, 2, Luo Wei1, 2
1. School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009; 2. Anhui New Energy Utilization and Energy Saving Laboratory, Hefei 230009
Abstract：Aiming at the problem of single-phase grounding fault line selection in small current grounding system that did not be solved thoroughly. This paper presents a fault line selection method of power distribution network based on improved Particle Swarm Optimization (PSO) to optimize Fuzzy Neural Network. By improving the fitness function and adaptive inertia weight of PSO, initial parameters and weights are optimized firstly, using the BP method to optimize the second time. The influence of Fuzzy Neural Network, the traditional PSO optimization of Fuzzy Neural Network and different network structures to network performance are discussed. The results of the study illustrate the improved PSO to optimize Fuzzy Neural Network is better than Fuzzy Neural Network and traditional PSO to optimize Fuzzy Neural Network in the term of line selection effect, can accurately, effectively, reliablely find fault line.
王磊, 曹现峰, 骆玮. 基于改进PSO优化模糊神经网络的配电网故障选线研究[J]. 电气技术, 2016, 17(3): 30-35.
Wang Lei, Cao Xianfeng, Luo Wei. Research on Fault Line Detection for Distribution Network based on Improved PSO to Optimize Fuzzy Neural Network. Electrical Engineering, 2016, 17(3): 30-35.
2016, Vol. 17 
