Assessing metaheuristic algorithms in determining dimensions of hybrid energy systems for isolated rural environments: Exploring renewable energy systems with hydrogen storage features

Abstract

Hydrogen presents a clean energy avenue capable of addressing the impending energy crises and environmental challenges. Given Turkey’s vast renewable energy potential, it can effectively meet its escalating electricity demand. In regions where grid connectivity is limited or costly, Hybrid Energy Systems (HRES) integrate a blend of energy matrices, thereby diminishing reliance on conventional sources. This study offers an intricate framework focusing on HRES optimization and energy flow management, emphasizing energy modules, such as wind, solar, biomass gasification, and fuel cells. Excess energy is converted to hydrogen for storage and is; subsequently utilized in fuel cells. The Annual Cost of the System (ACS) is a pivotal criterion during the optimization phase. This optimization encompasses variables such as power from wind turbines, energy output from solar panels, and hydrogen gas storage capacity, streamlined with Atom Search Optimization (ASO) methodology. Based on the consumption and meteorological data from 2022, a rigorous comparison of ten distinct optimization algorithms was conducted. The core objective is to satisfy the energy demand of the proposed hybrid system at a minimal cost. The results indicate that the advocated off-grid HRES emerges as the most cost-effective solution for the demarcated region, with the ASO algorithm demonstrating superiority in the convergence metrics for the objective function. The algorithms were implemented in a MATLAB simulation environment.