AI-Driven Intelligent Fault Detection and Diagnosis in a Hybrid AC/DC Microgrid

This paper focuses on the fault analysis and intelligent detection and diagnosis of faults in a hybrid AC/DC microgrid. The possibility of detecting and locating faults rapidly enables the grid controllers and energy management systems to accommodate the fault effects or isolate the faulty locations (parts) in a microgrid. This allows the rest of the microgrid to continue working without any serious interruption. The high effectiveness of the proposed scheme is illustrated under different fault conditions in an advanced microgrid benchmark model with wide variations in operating parameters and loads.