LVQ neural network approach for fault location of distribution network
According to the analysis on the difficulties of single phase grounding fault and the shortcomings of precise location using traveling wave signal in distribution network, a fault location method integrating the C-type of traveling wave location method with LVQ (Learn Vector Quantization) neural network is put forward. The aim is to combine different location methods to improve the accuracy of fault location. LVQ Neural Network is studied in this paper. The ability of feature extraction and pattern recognition is the characteristics of LVQ neural network, and it is applied to analyze reflected wave signals in different branches. In order to demonstrate the superiority of LVQ neural network, a classical BP (Back-Propagation) neural network has been developed to solve the same problem for comparison. The simulation results of ATP-EMTP and Matlab show that the LVQ neural network is quite effective and superior to BP neural network in fault location.
distribution networkfault locationC-type of traveling wave location methodLVQ neural networkBP neural network
国家科技期刊平台
NSTL
万方数据
维普
