Multi-objective optimization of thermal performance of packed bed latent heat thermal storage system based on response surface method

被引：53
作者：
Gao, Long [1 ]
Gegentana [1 ]
Liu, Zhongze [1 ]
Sun, Baizhong [1 ]
Che, Deyong [1 ]
Li, Shaohua [1 ]
机构：
[1] Northeast Elect Power Univ, Sch Energy & Power Engn, Jilin 132012, Jilin, Peoples R China
来源：
RENEWABLE ENERGY | 2020年 / 153卷
关键词：
Packed bed latent heat storage system; Thermal performance; Response surface method; Multi-objective optimization; ENERGY-STORAGE; PCM; FUTURE;
D O I：
10.1016/j.renene.2020.01.157
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
In this study, a simplified numerical model was developed to calculate the internal thermal distribution rules and thermal performance index of a packed bed latent heat thermal storage system (PBLHTES). The accuracy of the model was verified by comparing numerical results with experimental data. The response surface method (RSM) was applied to study and optimize the thermal performance of the PBLHTES. The quadratic regression model of three response indices was established based on 130 groups of Box -Behnken design (BBD) model scheme results, and rationality was verified through analysis of variance (ANOVA). The results showed the degree of influence of single factors and interactive factors on each performance index. The combined effect of the main interactive factors was analyzed in detail. The multi-objective optimized results indicated that effective heat storage time, effective heat storage, and exergy efficiency decreased by 30.24%, increased by 39.81%, and improved by 7.50%, respectively, compared with the basic working conditions before optimization. (C) 2020 Elsevier Ltd. All rights reserved.
引用
收藏
页码：669 / 680
页数：12
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