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.

中文翻译：

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使用考虑高温长期影响的多目标群体智能方法对离网混合可再生能源系统进行可靠且经济有效的优化设计


尽管混合可再生能源系统作为化石燃料系统的清洁替代品具有重要意义，但它们仍受到阻碍其最佳运行的各种因素的影响。因此，研究这些抑制因素的不利影响并提出合适的解决方案来增强这些系统在受试者中的性能至关重要。温度升高被认为是混合动力系统的一个重要影响因素，因为它们降低了能量提取效率并增加了总成本。本文建议将空调系统与离网混合能源系统集成，并使用多目标粒子群优化方法进行优化设计。其目的是解决高温的长期影响，在提高能源生产率和降低总生命周期成本之间实现平衡。引入新的创新模型来描述混合动力系统主要元件的能源效率和铅酸电池寿命服务随环境温度变化的演变。这项综合研究具有全球适用性，特别是在气候炎热的地区。作为案例研究，它在阿尔及利亚沙漠进行了测试。这项研究的主要结果表明，优化设计的空调离网混合动力系统的能源成本为每千瓦时0.27美元，比优化设计的非空调离网混合系统低2.44倍。 - 电网混合系统。此外，与第二个标准混合系统相比，第一个提出的离网混合系统实现了 99.1% 的年度能源需求覆盖率。 此外，第一个提出的混合系统中可再生能源贡献的总百分比为99%，而第二个标准混合系统中达到了96%。结果证实了优化设计的离网空调混合系统相对于优化设计的非空调离网混合系统的优越性。它效率更高，生命周期成本更低，可再生能源的贡献最大。