Abstract:
his paper addresses the critical problem of fault detection in DC zonal shipboard microgrids, which is essential for ensuring system reliability and operational safety. The proposed method detects faults by utilizing the high-frequency characteristics of estimated impedance. The technique involves Fast Fourier Transform analysis of current and voltage waveforms to extract high-frequency components before and after a fault. These features help identify the system’s high-frequency impedance via a communication system. Fault detection is achieved by comparing the estimated impedance with a predefined threshold. The performance of the method is evaluated using MATLAB/Simulink simulations and experimental implementations under various scenarios. Communication between components in the DC zonal microgrid is managed using the IEC 61850 standard. Results demonstrate the method’s effectiveness in detecting faults under diverse conditions, including variations in fault resistance, dynamic load behavior, changes in photovoltaic irradiation, system configuration alterations, noise immunity, and multi-fault scenarios. The method achieves fault clearance times ranging from 0.17 ms in MATLAB/Simulink simulations to 33–45 ms in experimental tests, showing its capability to enhance fault detection in complex DC microgrid environments.
