Correlation and K-means clustering based small current ground fault line selection algorithm

Abstract

The existing small current grounding line selecting technique has consequences by transition resistance, fault closure angles, and the fault location, and there is a problem of low selection accuracy, which is addressed by proposing a line-choosing algorithm that employs a combination of transient zero-sequential current (TZSC) waveform correlation and K-means clustering. First, to obtain the correlation coefficient matrix, the correlation analysis is performed for each line of the zero-sequence currents transient measurement values; second, to address the issue of the difficulties in manually setting the threshold, we apply the K-mean cluster analysis algorithm to group the row vectors of the correlation coefficients matrices; and finally, we output the label of the cluster to realize the fault line selection. Simulation and real-world fault data validate the method, showing that it is independent of transition resistance, fault closure angles, and fault location. It can achieve precise and dependable line selectivity.