Abstract In this paper, Jaya algorithm is applied to find an optimal unit sizing of renewable energy resources, including photovoltaic (PV) panels, wind turbines (WTs), and fuel cells (FCs) with the objective of reducing the consumer’s total annual cost in a stand-alone system. The system’s reliability is considered using the maximum allowable loss of power supply probability (LPSPmax) concept. The methodology is applied to real solar irradiation and wind speed data taken from Hawksbay, Pakistan. Simulation results achieved for low and high consumer’s load profiles show that when LPSPmax values are set to be 0% and 2%, the PV-FC is the most cost-effective system as compared to PV-WT-FC and WT-FC systems. Further, the results of Jaya algorithm are compared with a genetic algorithm, backtracking search algorithm, and particle swarm optimization.

中文翻译：

---

独立光伏、风力涡轮机和燃料电池系统的最佳尺寸

摘要 在本文中，Jaya 算法被应用于寻找可再生能源的最佳单位规模，包括光伏 (PV) 面板、风力涡轮机 (WT) 和燃料电池 (FC)，目的是降低消费者的年度总成本。一个独立的系统。系统的可靠性是使用最大允许的电源损耗概率 (LPSPmax) 概念来考虑的。该方法应用于从巴基斯坦霍克斯贝获得的真实太阳辐射和风速数据。针对低和高消费者负载曲线获得的仿真结果表明，当 LPSPmax 值设置为 0% 和 2% 时，与 PV-WT-FC 和 WT-FC 系统相比，PV-FC 是最具成本效益的系统。此外，将Jaya算法的结果与遗传算法、回溯搜索算法和粒子群优化进行了比较。