Optimal Sizing and Economic Assessment of a Hydrogen-Based Hybrid Renewable Energy System

Abstract

The growing emphasis on energy independence and sustainability has led to increased interest in hybrid renewable energy systems (HRESs) supported by long-term energy storage solutions. In this study, the optimal sizing of a standalone hybrid renewable energy system consisting of photovoltaic modules, wind turbines, an electrolyzer, hydrogen storage tanks and a fuel cell is examined. A comprehensive techno-economic optimization model is developed with the objective of reducing the Net Present Cost (NPC) and the Cost of Energy (COE) while ensuring an acceptable level of system reliability. To solve the optimization problem, three widely used metaheuristic techniques (Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Simulated Annealing (SA)) are implemented and comparatively evaluated based on their convergence characteristics and economic outcomes. The comparative analysis reveals that although all algorithms produce technically feasible solutions, PSO yields the most economical configuration with the lowest NPC and COE values. The findings demonstrate that the proposed optimization framework provides an effective and practical design approach for hydrogen-supported HRESs, supporting the development of reliable and sustainable off-grid power applications.