Characteristic Study and Non-invasive Detection of DC Arc-Fault in Microgrid

Abstract

Since a DC microgrid can connect renewable energy systems into distribution grids, researchers are focused on the techniques that can support the wide application of DC microgrids. However, DC arc faults can cause malfunctions and fire hazards in a DC microgrid. To detect the arc faults in DC microgrids, it is important to define their characteristics and develop a reliable arc-fault detection technique. Though the arc-fault characteristics of a DC microgrid should be further studied to develop a suitable arc model. In this paper, an arc model has been developed by combining the volt-ampere characteristics and frequency-domain features of arc faults. The simulation results prove that the arc-fault current can be accurately simulated by the derived arc model. According to the characteristics of arc faults, a DC arc-fault detection technique based on non-invasive magnetic-field sensing by magnetic sensors and spectrum energy integration is developed for DC microgrids. The experimental results validate that the arc faults can be effectively detected by the proposed technique. Hence, the developed arc model can be utilized to investigate the interaction between arc faults and DC microgrids. The proposed arc-fault detection method can improve the reliability of DC microgrids.