基于PSO-BP算法的高压输电线路故障分类

Fault Classification of High Voltage Transmission Line Based on PSO-BP Algorithm

在目前的电力系统中,高压输电线路担负着重要的任务,如果线路发生故障不能及时排除会造成巨大的影响。在对故障线路进行故障测距前,首先要进行故障类型的确定。将PSO(粒子群算法)和BP(神经网络)结合形成PSO-BP(粒子群神经网络)算法可以准确实现线路故障的分类。并利用小波变换对故障特征量进行提取。经仿真验证PSO-BP算法对线路故障类型分类的准确率更高。

In the current power system,the high voltage transmission line is responsible for the important task. If the fault of transmission line can not be eliminated in time,it may have a great impact. It is necessary to determine the fault type of the line before making the line fault location. The combination of PSO（particle swarm optimization） and BP（neural network） in order to form a PSO-BP（particle swarm neural network） algorithm could accurately classify the line fault. And wavelet transform was used to extract fault feature. The simulation results show that the PSO-BP algorithm is more accurate for the classification of line fault types.