Optimization of a hybrid renewable energy system for a rural community using PSO

• Published in: IOP conference series. Earth and environmental science Vol. 1199; no. 1; pp. 12034 - 12043
• Main Authors: Bismark, Kent Marc Kobe C., Caballa, Lorenzo Gabriel C., Yap, Christine Monique F., Peña, Robert Alfie S., Parocha, Raymark C., Macabebe, Erees Queen B.
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.07.2023
• Subjects: Algorithms; Alternative energy; Distributed generation; Electrical loads; Energy; Energy accessibility; energy and SDGs; Energy management; Energy utilization; Greenhouse gases; hybrid renewable energy systems; Hybrid systems; levelized cost of energy; Particle swarm optimization; Renewable energy sources; Renewable resources; Rural areas; Rural communities; Solar energy; Sustainable energy
• ISSN: 1755-1307; 1755-1315; 1755-1315
• DOI: 10.1088/1755-1315/1199/1/012034

With the Philippines’ goal towards developing sustainable energy systems, hybrid renewable energy systems (HRES) help the electrification goals of the nation especially in rural areas, while creating a safe and clean environment by decreasing greenhouse gases. The installation of HRES in these areas have the potential to improve energy access by utilizing renewable sources of energy, namely solar, wind, and hydro power. To ensure efficient management between the total power generation and total village load demand, a power network is built to reduce power interruptions due to the intermittent nature of the selected energy sources. This paper presents the integration of an energy management system (EMS) using particle swarm optimization (PSO) to direct and allocate the energy generated by a hybrid renewable energy system (HRES) designed through the HOMER Pro software. The results from the HOMER Pro simulations were used as input to the PSO algorithm to minimize the overall operational costs of the microgrid. The current and future load scenarios of the community were considered in the proposed HRES and the operational and levelized cost comparison are presented in this paper.