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Fast calculation of latent heat storage process in the direct steam generation solar thermal power system using a POD reduced-order model
Solar Energy ( IF 6.7 ) Pub Date : 2021-09-20 , DOI: 10.1016/j.solener.2021.09.042
Qianhao Ye 1 , Yajun Deng 2 , Tingyu Li 1 , Bo Yu 2 , Dongliang Sun 2 , Jinjia Wei 1, 3
Affiliation  

A Proper Orthogonal Decomposition (POD) reduced-order model for the latent heat storage process in a direct steam generation solar thermal power (DSG-STP) system is established based on the numerical simulation combined with the Lee model and enthalpy-porosity approach. Then, the computational accuracy and speed of the POD reduced-order model are examined by two unsteady-state cases. The research results show that the POD reduced-order model has good precision and fast computational speed. In the working conditions tested in this study, the relative mean error (RME) of POD-predicted temperature does not exceed 0.1% compared with the finite volume method’s results. Meantime, the POD calculation can improve the computational efficiency by hundreds of times (decrease from about 4 h to 45.865 s, about 314 times, for Case A). Thus, the POD reduced-order model has significant engineering value and is a promising means to accurately and efficiently solve the latent heat storage process in the DSG-STP system.



中文翻译:

基于POD降阶模型快速计算直接蒸汽发电太阳能热发电系统潜热储存过程

基于数值模拟,结合Lee模型和焓-孔隙率方法,建立了直接蒸汽发电太阳能热发电(DSG-STP)系统潜热存储过程的适当正交分解(POD)降阶模型。然后,通过两个非稳态情况检查 POD 降阶模型的计算精度和速度。研究结果表明,POD降阶模型具有较好的精度和较快的计算速度。在本研究测试的工作条件下,与有限体积法的结果相比,POD 预测温度的相对平均误差 (RME) 不超过 0.1%。同时,POD计算可以将计算效率提高数百倍(对于案例A,从大约4小时减少到45.865秒,大约314倍)。因此,

更新日期:2021-09-21
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