Design, modeling, and thermo-economic optimization of an innovative continuous solar-powered hybrid desalination plant integrated with latent heat thermal energy storage

•A novel hybrid continuous desalination plant driven by solar energy is studied.•A high-temperature phase change material is selected to store excess heat.•The Genetic algorithm is selected to conduct multi-objective optimization.•In the optimal design, the total produced potable water is 4352.87 m3...

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Veröffentlicht in:Applied thermal engineering 2023-01, Vol.219, p.119576, Article 119576
Hauptverfasser: Kaabinejadian, Amirreza, Moghimi, Mahdi, Fakhari, Iman
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Sprache:eng
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Zusammenfassung:•A novel hybrid continuous desalination plant driven by solar energy is studied.•A high-temperature phase change material is selected to store excess heat.•The Genetic algorithm is selected to conduct multi-objective optimization.•In the optimal design, the total produced potable water is 4352.87 m3/day. Ever-increasing needs for freshwater over the globe have made scientists investigate and find out viable solutions to overcome this concern. In line with this fact, multi-objective optimization of a solar-assisted hybrid desalination plant, which encompasses multi-effect distillation with thermal vapor compression and humidification-dehumidification units, was carried out during this study. Parabolic trough solar collectors play the role of a supplier of required input energy to run this system. In addition, there is a heating and storage unit, which includes a latent heat thermal storage tank to store the excess heat gained by solar collectors and an auxiliary boiler to assist in supplying the required heat for desalination units. Design parameters such as Parabolic trough solar collectors rows, phase change materials, number of multi-effect distillation system effects, motive steam flow rate, and last effect brine temperature of multi-effect distillation system which have the greatest impact on the performance of the system are selected. The non-dominated sorting genetic algorithm was employed to conduct multi-objective optimization. According to the optimization results, the total cost rate of the system and the sustainability index is 0.548 $/s and 1.54 respectively. In addition, adding the humidification-dehumidification unit to the system contribute to producing 0.5% more fresh water and brings 0.1% extra cost.
ISSN:1359-4311
DOI:10.1016/j.applthermaleng.2022.119576