Desalination ( IF 8.3 ) Pub Date : 2023-06-28 , DOI: 10.1016/j.desal.2023.116808 Khalid Almutairi
The global scarcity of fresh water has prompted the development of innovative strategies for establishing affordable and efficient desalination systems that utilize waste heat from industrial processes. This study presents a novel combination of a geothermal-driven dual-loop organic Rankine cycle and liquefied natural gas (LNG) regasification process intended for electricity, desalinated water, and hydrogen production. The integration of diverse energy sources holds the capability to reduce dependence on traditional fossil fuels and promote a more sustainable and diversified energy portfolio, conducive to ecological well-being. In the suggested approach, a thermoelectric generator (TEG) is employed to harness the thermal contrast present between the residual heat of the geothermal process and the cold LNG stream, which reduces irreversibility and increases the system's power output. After examining the effect of key parameters on the system's performance, a data-driven approach is adopted in which the system's performance is predicted based on artificial neural networks (ANNs). According to the results, the primary generated power, desalinated water production rate, total cost rate, and cooling load are 5.15 MW, 127.31 m3/h, 188.22 $/h, and 2.92 MW, respectively. Also, the findings of the financial investigation demonstrate that the electrolysis unit, with an hourly cost rate of 85.2 $, constitutes more than 45 % of the total cost rate. In addition, the optimization of the system is performed in three distinct cases, wherein each case pertains to a different objective. In optimal conditions, the amount of produced desalinated water and the total cost rate are 153.89 m3/h and 153.58 $/h, respectively.
中文翻译:
环保利用液化天然气再气化工艺和地热双回路动力循环进行淡化水和氢气生产
全球淡水稀缺促使人们制定创新战略,建立可负担且高效的海水淡化系统,利用工业过程中的废热。本研究提出了地热驱动双回路有机朗肯循环和液化天然气 (LNG)再气化工艺的新颖组合,旨在用于电力、淡化水和氢气生产。多种能源的整合有能力减少对传统化石燃料的依赖,促进更加可持续和多样化的能源组合,有利于生态福祉。在建议的方法中,采用热电发电机(TEG)来利用地热过程的余热和冷液化天然气流之间存在的热对比,从而减少不可逆性并增加系统的功率输出。在检查了关键参数对系统性能的影响后,采用数据驱动的方法,其中基于人工神经网络(ANN)。结果显示,一次发电量、淡化水产率、总成本率和冷负荷分别为5.15 MW、127.31 m3/h、188.22 $/h和2.92 MW。此外,财务调查结果表明,电解装置的每小时成本为 85.2 美元,占总成本的 45% 以上。此外,系统的优化是在三种不同的情况下执行的,其中每种情况涉及不同的目标。在最佳条件下,淡化水产量和总成本分别为153.89 m 3 /h和153.58 $/h。