Reliable and cost-effective optimal design of an off-grid hybrid renewable energy system using a multi-objective swarm intelligence method considering long-term effects of high temperature

• Published in: Energy conversion and management Vol. 315; p. 118754
• Main Authors: Houam, Yehya, Bouarroudj, Noureddine, Djari, Abdelhamid, Si Tayeb, Abdelkader
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.09.2024
• Subjects: administrative management; air; air conditioning; Air-conditioned hybrid system; algorithms; ambient temperature; batteries; case studies; cost effectiveness; energy costs; energy efficiency; fossil fuels; Hybrid PV/Wind/Bat/DG system; Life cycle costs; Long-term effects of high temperature; Multi-objective particle swarm optimization; Reliability; renewable energy sources; swarms; system optimization; Hybrid PV/Wind/Bat/DG system; Multi-objective particle swarm optimization; Long-term effects of high temperature; Reliability; Life cycle costs; Air-conditioned hybrid system
• ISSN: 0196-8904
• DOI: 10.1016/j.enconman.2024.118754

•Show long-term high temperature effects on hybrid energy systems.•An optimal hybrid system design using multi-objective swarm intelligence.•An air-conditioned hybrid system is best for hot climates.•Air conditioning in hybrid systems increases efficiency and cuts energy costs.•Novel temperature-based energy efficiency models in hybrid systems introduced. Despite the significant importance of hybrid renewable energy systems as a clean alternative to fossil fuel systems, they are affected by various factors obstructing their optimal operation. Hence, it is crucial to investigate the adverse effects of these inhibiting factors and suggest suitable solutions to enhance the performance of these systems in subject. Elevated temperatures are regarded as a significant influencing factor on hybrid systems, as they reduce energy extraction efficiency and increase total costs. This paper suggests integrating air conditioning systems with off-grid hybrid energy systems, which are optimally designed using the multi-objective particle swarm optimization method. The aim is to address the long-term effects of high temperature, achieving a balance between enhancing energy productivity and reducing total life cycle costs. New innovative models are introduced to describe the evolution of the energy efficiency of the main elements of hybrid systems and lead-acid battery life service with changes in ambient temperature. This comprehensive study has global applicability, particularly in regions with hot climates. It was tested in the Algerian desert as a case study. The main findings of this study revealed that the energy cost of the optimally designed air-conditioned off-grid hybrid system amounted to 0.27 US$ per kilowatt-hour, which is 2.44 times lower than that of an optimally designed non-air-conditioned off-grid hybrid system. Additionally, the first proposed off-grid hybrid system achieved a higher annual percentage of energy demand coverage of 99.1% compared to the second standard hybrid system. Furthermore, the total percentage of renewable energy contribution in the first proposed hybrid system is 99%, whereas it reached 96% in the second standard hybrid system. The results confirm the superiority of the optimally designed off-grid air-conditioned hybrid system over the optimally designed non-air-conditioned off-grid hybrid system. It is more efficient, has lower life cycle costs, and highest contribution of renewable energies.