Research on the Classification of Distribution Network Fault Based on Convolutional Neural Network
In order to classify efficiently and accurately distribution network fault,a distribution network fault classification method based on convolutional neural network is proposed.The proposed method can directly process the raw data samples of the three-phase voltage and current signals,and output all types of distribution network fault types including no faults.The test results of applying the 10-fold cross-validation method show that the accuracy of the proposed method is 99.52％.In com-parison experiments with fault classification methods based on traditional machine learning models,the proposed method shows better classification performance in terms of both accuracy and computational efficiency.The proposed method is applied to power distribution systems with unintegrated and integrated distributed power generation,and achieves classification accuracies of 99.92％ and 99.97％.
power distribution networkfault classificationconvolutional neural networkdistributed generatormachine learning
万方数据
维普
