Two‐layer coordination architecture HIF detection with µPMU data

Abstract

The detection of high-impedance fault (HIF) on distribution network has been one of the most difficult problems. This study presents a data-driven method for HIF detection by using single-ended micro-phasor measurement unit (µPMU). This approach is based on the two-layer coordination architecture, local side with μPMUs and master station for further analysis. At the local side, the μPMUs gather the synchronous data and achieve feature extraction with k-means clustering algorithm and principal component analysis. For determining the amounts of data categories, the authors adopt a method based on silhouette coefficient. Meanwhile, send the characteristics to the master station, then detect the HIF fault through the support vector machine. Finally, the method was tested on a 34 nodes distribution network in PSCAD/EMTDC. The results justify the effectiveness and the proposed detection scheme has >85% accuracy.