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Optimal Design of Hybrid Renewable Energy System for a Reverse Osmosis Desalination System in Arar, Saudi Arabia
Arabian Journal for Science and Engineering ( IF 2.6 ) Pub Date : 2021-04-13 , DOI: 10.1007/s13369-021-05645-0
Ali M. Eltamaly , Emad Ali , Mourad Bumazza , Sarwono Mulyono , Muath Yasin

Saudi Arabia tries to build local desalination water stations to supply water to remote areas. Due to the low cost and energy requirements of reverse osmosis (RO) desalination technology, it has been used to supply fresh water to Arar City in the northeast of Saudi Arabia. In this paper, it is proposed to provide an average of 1000 cubic meters of water per day by using autonomous hybrid renewable energy system (RES). This proposed system contains wind turbines (WTs), photovoltaic (PV), battery, and it is designed to feed the RO system with the energy adequate to produce the required amount of fresh water for the minimum cost and minimum loss of supply probability. The proposed system was designed to generate 2440 kW power to produce this amount of water. Matching study between the site and the best WT among 10 market-available WTs is introduced. Three optimization strategies were used and compared for the design of the proposed system to ensure that no premature convergence can occur. These strategies consisted of two well-known techniques, particle swarm optimization and bat algorithm (BA), and a relatively new technique: social mimic optimization. The simulation results obtained from the proposed system showed the superiority of using a RES for feeding a RO desalination power plant in Arar City, and they also showed that the BA is the fastest and most accurate optimization technique to perform this design problem compared with the other two optimization techniques. This detailed analysis shows that the cost of production of fresh water is $0.745/m3.



中文翻译:

反渗透海水淡化系统混合可再生能源系统的优化设计

沙特阿拉伯试图建立当地的海水淡化站,以向偏远地区供水。由于反渗透(RO)淡化技术的低成本和能源需求,它已被用来为沙特阿拉伯东北部的Arar City提供淡水。在本文中,建议通过使用自主混合可再生能源系统(RES)每天平均提供1000立方米的水。此提议的系统包含风力涡轮机(WTs),光伏(PV),电池,并且旨在为RO系统提供足够的能量,以产生所需的淡水量,从而以最低的成本和最小的供应概率损失。拟议中的系统旨在产生2440 kW的功率来产生这种量的水。介绍了站点与10个市场可用的WT中最佳WT之间的匹配研究。使用了三种优化策略,并比较了所建议系统的设计,以确保不会发生过早的收敛。这些策略包括两种众所周知的技术:粒子群优化和bat算法(BA),以及一种相对较新的技术:社交模仿优化。从提出的系统获得的仿真结果表明,使用RES为阿拉尔市的RO海水淡化发电厂供电具有优越性,并且他们还表明,与其他方法相比,BA是解决这一设计问题的最快,最准确的优化技术两种优化技术。这项详细分析显示,淡水的生产成本为0.745美元/米 这些策略包括两种众所周知的技术:粒子群优化和bat算法(BA),以及一种相对较新的技术:社交模仿优化。从提出的系统获得的仿真结果表明,使用RES为阿拉尔市的RO海水淡化发电厂供电具有优越性,并且他们还表明,与其他方法相比,BA是解决这一设计问题的最快,最准确的优化技术。两种优化技术。这项详细分析显示,淡水的生产成本为0.745美元/米 这些策略包括两种众所周知的技术:粒子群优化和bat算法(BA),以及一种相对较新的技术:社交模仿优化。从提出的系统获得的仿真结果表明,使用RES为阿拉尔市的RO海水淡化发电厂供电具有优越性,并且他们还表明,与其他方法相比,BA是解决这一设计问题的最快,最准确的优化技术。两种优化技术。这项详细分析显示,淡水的生产成本为0.745美元/米 从提出的系统获得的仿真结果表明,使用RES为阿拉尔市的RO海水淡化发电厂供电具有优越性,并且他们还表明,与其他方法相比,BA是解决这一设计问题的最快,最准确的优化技术。两种优化技术。这项详细分析显示,淡水的生产成本为0.745美元/米 从提出的系统获得的仿真结果表明,使用RES为阿拉尔市的RO海水淡化发电厂供电具有优越性,并且他们还表明,与其他方法相比,BA是解决这一设计问题的最快,最准确的优化技术。两种优化技术。这项详细分析显示,淡水的生产成本为0.745美元/米3

更新日期:2021-04-13
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