Fault Detection and Diagnosis in Power Electronic Converters at Microgrid Level Based on Filter Bank Approach

This paper aims at proposing a novel fault detection and diagnosis approach for the internal components of power electronic converters in a microgrid framework. A cluster of interconnected loads and distributed energy resources, and battery energy storage system is considered as a hybrid AC/DC microgrid. The proposed fault detection and diagnosis scheme aims at indicating the occurrence of faults in the internal components of the power electronic converter as well as determining the magnitude of the faults in the presence of uncertainties and dynamic load disturbances. For this purpose, the power spectrum estimations of signals based on filter bank approach are used. The effectiveness of the designed scheme and its robustness under microgrid uncertainties and disturbances are demonstrated in an advanced microgrid benchmark model implemented in MATLAB/Simulink environment.