Artificial Neural Network Based Fault Detection and Fault Location in the DC Microgrid

Abstract In DC microgrid, power electronic devices may suffer from over current during short circuit faults. Since DC bus systems cannot sustain high fault currents, suitable protection strategy in DC lines is indispensable. This paper presents a novel use of artificial neural network (ANN) for fault detection and fault location in a low voltage DC bus microgrid system. In the proposed scheme, the faults on DC bus can be fast detected and then isolated without de-energizing the entire system, hence achieving a more reliable DC microgrid. The neural network is trained based on the different short circuit faults in DC bus to ensure its validity. A microgrid with ring DC bus, which is segmented into overlapping nodes and linked with circuit breakers, is built in PSCAD/EMTDC to test the performance of the protection scheme.