Optimal Load-Frequency Control of Interconnected Microgrids Using an EEFO-Optimized Fuzzy-PIDF Controller

This paper presents an Electric Eel Foraging Optimization (EEFO) fuzzy logic-assisted proportional–integral–derivative (PID) controller incorporating a derivative filter (Fuzzy-PIDF) to improve load-frequency regulation of interconnected microgrid systems. There are two related areas in the system under study: photovoltaic generation and wind energy conversion systems, as well as electrical energy storage units based on batteries and superconducting magnetic energy storage (SMES), and diesel generators. A dynamic system is established to represent changes in frequency and power exchange. EEFO is employed to tune not only the PIDF gains and fuzzy scaling factors but also the fuzzy membership functions using an objective function based on the changes in inter-area power and frequency. Moreover, the controller is assessed under a 5% demand disturbance, as well as various disturbance magnitudes, parameter variations, variable loading conditions, and renewable-generation fluctuations. Comparative studies are conducted against the Fuzzy-PIDF controllers configured using Competition Over Resources (COR) and the Marine Predators Algorithm (MPA). Lower-frequency and inter-area power deviations are achieved using the EEFO-Fuzzy-PIDF controller across the investigated operating scenarios.