Optimizing separate and combined grids for cost-effective hybrid renewable energy electrification in Mogadishu, Somalia

Abstract

Expanding access to affordable, reliable, and sustainable electricity is an urgent priority in Somalia, which suffers from high energy costs and climate vulnerability despite negligible emissions. Therefore, this study employs MATLAB simulation software and three algorithms—particle swarm optimization (PSO), genetic algorithm, and simulated annealing—to determine optimal separate and combined grid designs for a hybrid renewable energy system in Mogadishu, Somalia. Four system configurations are assessed, namely, utilities—diesel-alone, Photovoltaic (PV)–diesel hybrid, wind–diesel hybrid, and PV–wind–diesel hybrid across the grids of three utilities—Benadir Electric Company, Mogadishu Power Supply, and Blue-Sky Energy. The algorithms evaluate technical feasibility, economic viability, and system reliability to identify the most suitable configurations. Forty-eight systems are analyzed. The combined PV/wind/diesel grid optimized with PSO is most effective, reducing the net present cost by 32%–47% and levelized cost of electricity by 41%–60% compared to diesel-only systems while maintaining reliability. Greenhouse gas emissions decrease by 38%–59% with the hybrid system.