EMD/HT-based local fault detection in DC microgrid clusters

DC faults can create serious damages if not detected and isolated in a short time. This paper proposes a fault detection technique for DC faults to enhance the protection of DC microgrid clusters. To detect such faults accurately and quickly, a DC fault detection scheme using empirical mode decomposition and Hilbert transform is proposed. Due to the strict time limits for fault interruption caused by fast high-rising fault currents in DC systems, DC microgrid clusters' protection remains a challenging task. Furthermore, high impedance faults (HIFs) in DC systems cause a small change in the current, which can damage the power electronic converters if not detected in time. Therefore, this paper proposes a local scheme for the fast detection of faults including HIFs in DC microgrid clusters. Both simulation and experimental results using a scaled DC microgrid cluster prototype and considering several scenarios (such as low impedance faults, HIFs, noise, overload, and bad calibration of sensors) demonstrate the successful and fast detection (less than 2 ms) of DC faults by the proposed method. Compared with other techniques, the proposed scheme presents its merits from the viewpoints of accuracy and speed.