Enhanced load frequency regulation in microgrids with renewable energy sources and electric vehicles

Microgrid frequency control faces challenges due to load fluctuations and the intermittent nature of Renewable Energy Sources (RESs). The Load Frequency Control (LFC) scheme has been a profoundly investigated matter for decades for achieving a consistent frequency. This study introduces a novel cascaded Integral-Proportional-Proportional Derivative with Filter (I-P)-PDN controller designed to mitigate frequency deviations in microgrids incorporating Photovoltaic (PV) and Wind Turbine Generator (WTG), Fuel Cells (FCs), Electric Vehicles (EVs), Battery Energy Storage Systems (BESS), and Diesel Engine Generators (DEGs). To optimize the controller's parameters, the recently introduced Black-winged Kite Algorithm (BKA) is employed for its superior search efficiency and quick convergence. Simulation results show that the (I-P) cascaded PDN controller significantly outperforms existing controllers, such as PID, and PI-based models, by reducing frequency deviations, improving settling time, and minimizing overshoot and error indices. There is notable 77% reduction in overshoot (OSH) and 52% decrease in undershoot (USH) in tie-line power variations. Moreover, the Integral Absolute Error (IAE) is reduced by 42.3%, the Integral Time weighted Absolute Error (ITAE) by 85%, and the Integral Squared Error (ISE) by 98%. The study also examines the role of EVs as flexible energy storage, demonstrating their contribution to system resilience and stability. This approach offers a robust solution for effective frequency regulation in modern microgrids, ensuring reliable performance in dynamic conditions.