A data-driven method to detect and localize the single-phase grounding fault in distribution network based on synchronized phasor measurement

Abstract

The single-phase grounding fault of power systems is influenced by a variety of factors, resulting from the developing sizes and increasing complexity of power systems. In order to take advantage of big data in power systems, we propose a revised method with the use of synchronized phasor measurement. The data-driven method is designed to detect and localize the single-phase grounding fault, which reveals the correlation between eigenvalues and status of power systems. First, it calculates the contribution of the fault to each node; it then combines with a split window to monitor power systems in real time and to detect fault more efficiently. Based on the correlation between the elements of the matrix, it is robust against bad data and highly sensitive to weak signals. In general, the proposed method is applicable to various faults and well-functioning with real-time analysis. We test the proposed method with case studies from a distribution network with 80 nodes.