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Dynamic simulation and multi-objective optimization of a solar-assisted desiccant cooling system integrated with ground source renewable energy
Applied Thermal Engineering ( IF 6.1 ) Pub Date : 2020-03-16 , DOI: 10.1016/j.applthermaleng.2020.115210
Saeed Rayegan , Shahrooz Motaghian , Ghassem Heidarinejad , Hadi Pasdarshahri , Pouria Ahmadi , Marc A. Rosen

This study presents a dynamic simulation-optimization of a solar-assisted desiccant cooling system integrated with a ground source heat exchanger (SDCS-GSHE). Solar and ground source energies are used for regenerating the desiccant wheel (DW) and a pre-cooling process, respectively. The system is considered as an alternative for extremely hot and humid regions. Determinant design parameters of the SDCS-GSHE that are associated with the DW, GSHE, and solar loop components directly affect the system behavior and, consequently, the provided thermal comfort, as well as the solar fraction (SF). Therefore, a multi-objective genetic algorithm optimization is invoked to determine all viable optimum design parameters to set up the system. Also, an economic assessment of the system is performed to demonstrate its economic feasibility. With the results, the optimum regeneration temperature, number of ground boreholes, collector area can be determined based on the required level of thermal comfort and the SF. The results reveal that, in the absence of the GSHE, the system cannot provide thermal comfort in extremely humid regions even with high regeneration temperatures (around 120 °C). Instead, using the GSHE dramatically improves the established thermal comfort. For regeneration temperatures below 90°C, it is determined that the total necessary energy can be supplied entirely by solar energy. For the best case, in which the system successfully provides thermal comfort, the cost payback period for the system is found to be 5.7 years.



中文翻译:

集成了地源可再生能源的太阳能辅助干燥剂冷却系统的动态仿真和多目标优化

这项研究提出了集成有地面源热交换器(SDCS-GSHE)的太阳能辅助干燥剂冷却系统的动态仿真优化。太阳能和地面能源分别用于再生干燥剂轮(DW)和预冷过程。该系统被认为是极热和潮湿区域的替代方案。与DW,GSHE和太阳能回路组件关联的SDCS-GSHE的确定性设计参数直接影响系统性能,并因此影响所提供的热舒适度以及太阳能分数(SF)。因此,调用多目标遗传算法优化来确定所有可行的最佳设计参数以建立系统。同样,对该系统进行了经济评估,以证明其经济可行性。结果,可以根据所需的热舒适度和SF来确定最佳再生温度,地面钻孔数量,集热器面积。结果表明,在没有GSHE的情况下,即使在较高的再生温度(约120°C)下,该系统也无法在极其潮湿的区域提供热舒适性。相反,使用GSHE可显着改善既定的热舒适性。对于低于90°C的再生温度,可以确定总所需能量可以完全由太阳能提供。在最好的情况下,系统成功地提供了热舒适性,发现该系统的成本回收期为5.7年。结果表明,在没有GSHE的情况下,即使在较高的再生温度(约120°C)下,该系统也无法在极其潮湿的区域提供热舒适性。相反,使用GSHE可以显着改善既定的热舒适性。对于低于90°C的再生温度,可以确定总所需能量可以完全由太阳能提供。在最好的情况下,系统成功地提供了热舒适性,发现该系统的成本回收期为5.7年。结果表明,在没有GSHE的情况下,即使在较高的再生温度(约120°C)下,该系统也无法在极端潮湿的区域提供热舒适性。相反,使用GSHE可以显着改善既定的热舒适性。对于低于90°C的再生温度,可以确定总所需能量可以完全由太阳能提供。在最好的情况下,系统成功地提供了热舒适性,发现该系统的成本回收期为5.7年。已确定总所需能量可以完全由太阳能提供。在最好的情况下,系统成功地提供了热舒适性,发现该系统的成本回收期为5.7年。已确定总所需能量可以完全由太阳能提供。在最好的情况下,系统成功地提供了热舒适性,发现该系统的成本回收期为5.7年。

更新日期:2020-03-16
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