Detection of high-impedance fault in low-voltage DC distribution system via mathematical morphology

Abstract

This study presents a method for high-impedance fault (HIF) detection in a low-voltage DC (LVDC) distribution system via mathematical morphology (MM), which is composed of two elementary transformations, namely, dilation and erosion. Various MM-based filters are used to detect abnormal signals of current waveform. The LVDC distribution system, including power conversion devices, such as AC/DC and DC/DC converters, is modelled with electromagnetic transient program (EMTP) software to verify the proposed method. The HIF arc model in the DC system is also implemented with EMTP/MODELS, which is a symbolic language interpreter for EMTP. Simulation results show that the proposed method can be applied to detect HIF effectively in the LVDC distribution system.