Co-Optimized Energy Storage Design of Islanded Hybrid Microgrids Using Synergistic AI Techniques: A Case Study for Remote Electrification

Most of the world's energy needs are in rural and isolated regions. Hybrid energy systems (HES), combining different types of renewable energy and energy storage technologies, can provide a viable solution for off-grid electrification in rural areas. This paper evaluates the performance analysis, and optimization of an autonomous hybrid system incorporating solar-photovoltaic (PV) array, wind-turbine, storage batteries, and backup generator. It focuses on the case study of an isolated village in Namibia, characterized by high solar irradiation levels and limited availability of wind power. The local load profile, solar irradiation, and wind speed data were employed to ensure precise system model. Using HOMER Pro software for hybrid system simulation, a more advanced optimization was carried out utilizing two metaheuristic algorithms, namely, the Grey Wolf Optimization (GWO), and Harris Hawks Optimization (HHO). The results indicate the best performance was obtained with the GWO algorithm, which achieved a minimum energy cost (COE) of $0.268/kWh. This study demonstrates that advanced techniques can enhance the economic and technical efficiency of hybrid systems to achieve a sustainable electricity supply in rural areas.