Comparative Analysis of PSO and HOMER Pro for Optimizing Hybrid Energy System Sizing in Residential Applications

Abstract

Hybrid Renewable Energy Systems (HRESs) are an attractive solution to ensure reliable, efficient, and sustainable energy delivery to remote areas. In contrast, finding the best optimal sizing solution is not easy due to the differing design approaches of commercial tools such as HOMER Pro and algorithmic tools such as Particle Swarm Optimization (PSO) algorithms. This work attempts to critically evaluate and compare HOMER Pro and PSO techniques for sizing HRE systems involving wind turbines, solar PV systems, energy storage, and diesel power, and is focused on the analysis of three primary considerations: Levelized Cost of Energy (LCOE), Net Present Cost (NPC), and the fraction of the generated power from renewables. The comparison between PSO and HOMER Pro suggests that PSO provides approximately 5 % saving on NPC and more reliable systems than HOMER Pro. HOMER Pro is more efficient on NPC but has high LCOE and zero fraction of renewables on cost consideration.