Optimizing off-grid residential hybrid systems with and without energy storage: A constriction-coefficient PSO approach to cost, reliability, and emissions trade-offs

In response to the growing demand for sustainable and cost-effective energy solutions, hybrid energy systems that integrate solar, wind, and diesel generators provide an alternative to diesel-only supply for residential buildings, particularly in remote areas. This study examines the optimal design and performance of five stand-alone hybrid systems, with and without battery energy storage (BES), with emphasis on reliability, cost, and environmental impact. An improved constriction-coefficient Particle Swarm Optimization (ICC-PSO) method is proposed for system optimization, and its performance is compared with Harmony Search, Simulated Annealing, standard PSO, and five PSO variants. The effects of reliability limits, fuel price, photovoltaic cost, and CO 2 emission penalties are also examined. The results show that the solar/BES/diesel configuration reduces total net annual cost (TNAC) by up to 36.6% and CO 2 emissions by 61.7% relative to diesel-only, while maintaining high reliability. Across the tested cases, ICC-PSO yields lower TNAC and faster convergence than the benchmarked algorithms. These findings indicate that battery-integrated hybrid systems can support off-grid residential energy planning under varying economic, policy, and reliability conditions.