OPTIMAL DESIGN OF STANDALONE HYBRID RENEWABLE ENERGY SYSTEMS USING ANT COLONY OPTIMIZATION FOR RURAL ELECTRIFICATION IN NIGERIA
Rural electrification remains a pressing challenge in developing countries, particularly in Sub-Saharan Africa, where over 80 million Nigerians still lack reliable electricity access. This study addresses the complex, nonlinear, and multi-objective problem of optimizing standalone hybrid energy systems (HES) that integrate solar photovoltaics (PV), wind turbines (WT), battery energy storage (BESS), and diesel generator (DG) backup for rural electrification. Traditional optimization techniques such as Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) often face limitations in convergence speed, diversity of solutions, and robustness against local minima. To overcome these challenges, an Ant Colony Optimization (ACO)-based framework is developed for the optimal system sizing and dispatch of standalone HES, benchmarked directly against PSO under identical simulation conditions. Mathematical models of PV, WT, BESS, and DG are integrated within an energy management strategy (EMS) that ensures load balance and reliability. Simulation results show that ACO achieved a Net Present Cost (NPC) of $92,500 and a Levelized Cost of Energy (LCOE) of $0.243/kWh, compared to $101,300 NPC and $0.268/kWh LCOE for PSO, while reducing the Loss of Power Supply Probability (LPSP) from 2.1% to 0.9%. Convergence speed improved by 27%, and robustness analysis confirmed lower variance across multiple runs. These findings highlight ACO�s superiority in efficiency, reliability, and adaptability, establishing it as a powerful optimization tool for sustainable rural electrification in Nigeria and other developing regions.
Authors : Shettima, K.A., Musa, B.U., Tijjani, M.M. and Goni, S.A.
Category : Open Access Volume (Issue) : 11(2) Date Uploaded : 14th October 2025