Optimization of a hybrid renewable energy system for off-grid residential communities using numerical simulation, response surface methodology, and life cycle assessment

• Published in: Renewable energy Vol. 236
• Main Authors: Roshani, Amir Salek, Assareh, Ehsanolah, Ershadi, Ali, Carvalho, Monica
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.12.2024
• Subjects: And air conditioning; Global warming potential; Heating; Multi-criteria optimization; Off-grid system; Renewable energy systems; Ventilation; Global warming potential; Heating; Renewable energy systems; Multi-criteria optimization; Ventilation; And air conditioning; Off-grid system
• ISSN: 0960-1481
• DOI: 10.1016/j.renene.2024.121425

This paper presents an optimized hybrid renewable energy system tailored for off-grid residential communities, integrating wind, solar, and hydrogen technologies to meet electricity, cooling, heating, and water needs. The proposed optimization methodology combines numerical simulation, response surface methodology (RSM), and life cycle assessment (LCA), ensuring robust performance across diverse conditions. Key components include fuel cells, reverse osmosis systems, heat pumps, photovoltaic/thermal solar collectors, wind turbines, and hydrogen generation systems. The optimization process targets critical variables such as PVT panel area, the number of wind turbines, and fuel cell power. The optimal configuration was found to include 24 small-scale wind turbines, 159.46 m2 of PVT collectors, and 79.73 kW of fuel cell power. This configuration generated surplus electricity with net electricity usage (NEU) values of −123084.27 kWh/year in New York, −224245.29 kWh/year in Forks, and −215949.30 kWh/year in Santa Barbara. Additionally, the optimized systems achieved a significant reduction in life cycle cost (LCC), with Forks showing the lowest LCC at 304428.97 USD. The environmental impact was also minimized using the novel optimization approach, with the optimized systems achieving negative 100-year global warming potential (GWP100) values, indicating a net reduction in greenhouse gas emissions.