Research on arc grounding identification method of distribution network based on waveform subsequence segmentation-clustering

Abstract

The traditional method of detecting fault current based on threshold judgment method is limited by the current size and is easily disturbed by noise, and it is difficult to adapt to the arc ground fault detection of the distribution network. Aiming at this problem, this paper proposes a single-phase arc-optic ground fault identification method based on waveform subsequence splitting fault segmentation, combined with three-phase voltage-zero sequence voltage waveform feature extraction clustering. First of all, the waveform fault segment is segmented and located, secondly, the characteristic indexes of the time domain and frequency domain of the combined three-phase voltage-zero sequence voltage waveform are established, and the multidimensional feature distribution is reduced by the principal component analysis method, and finally, the characteristic distribution after the dimensionality reduction is identified by the K-means clustering algorithm based on the waveform subsequence. Experimental results show that the arc light grounding fault identification method proposed in this paper achieves 97.12% accurate identification of the test sample.