Optimal Sizing of Electrical and Hydrogen Generation Feeding Electrical and Thermal Load in an Isolated Village in Egypt Using Different Optimization Technique

This paper analyzes the functional feasibility and strategic value of hybrid hydrogen storage and photovoltaic (PV) energy systems at isolated areas, specifically at Egypt’s Shalateen station. The paper is significant as it formulates a solution to the energy independence coupled with economic feasibility issue in regions where the basic energy infrastructure is non-existent or limited. Through the integration of a portfolio of advanced optimization algorithms—Differential Evolution (DE), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Multi-Objective Genetic Algorithm (MOGA), Pattern Search, Sequential Quadratic Programming (SQP), and Simulated Annealing—the paper evaluates the performance of two scenarios. The first evaluates the PV system in the absence of hydrogen production to demonstrate how system parameters are optimized by Pattern Search and PSO to achieve a minimum Cost of Energy (COE) of 0.544 USD/kWh. The second extends the system to include hydrogen production, which becomes important to ensure energy continuity during solar irradiation-free months like those during winter months. In this scenario, the same methods of optimization enhance the COE to 0.317 USD/kWh, signifying the economic value of integrating hydrogen storage. The findings underscore the central role played by hybrid renewable energy systems in ensuring high resilience and sustainability of supplies in far-flung districts, where continued enhancement by means of optimization is needed to realize maximum environmental and technological gains. The paper offers a futuristic model towards sustainable, dependable energy solutions key to the energy independence of the future in such challenging environments.