电力学报2018，Vol.33Issue(2)：116-122,133,8.
基于传统BP神经网络和经云遗传优化的神经网络配电网故障定位研究
Research on Fault Location of Distribution Network Based on Traditional BP Neural Network and Neural Network Optimized by Cloud Genetic Algorithm
韩娜 1邹红波 1喻圣1
作者信息
- 1. 三峡大学电气与新能源学院, 湖北 宜昌 443000
- 折叠
摘要
Abstract
Aiming at the problem of distribution network fault location, a positioning model based on BP neural network with simple structure and strong plasticity in artificial neural network(ANN)is proposed. BP network model is established and the trained BP network model is improved and applied to the same simple distribution network system through cloud genetic algorithm. Feature extraction and pattern recognition are respectively performed on the reflection information of different branches. By comparing the two algorithms The comparison between the training curve and the diagnostic accuracy reflects the efficiency and accuracy of the optimization algorithm and finally determines the actual output value of the diagnosis to determine and pinpoint the fault branch.关键词
故障定位/BP神经网络/云遗传/配电网Key words
fault location/BP neural network/cloud inheritance/power distribution network分类
信息技术与安全科学引用本文复制引用
韩娜,邹红波,喻圣..基于传统BP神经网络和经云遗传优化的神经网络配电网故障定位研究[J].电力学报,2018,33(2):116-122,133,8.
