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

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  • Gao, Long
  • Gegentana,
  • Liu, Zhongze
  • Sun, Baizhong
  • Che, Deyong
  • Li, Shaohua

Abstract

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.

Suggested Citation

  • Gao, Long & Gegentana, & Liu, Zhongze & Sun, Baizhong & Che, Deyong & Li, Shaohua, 2020. "Multi-objective optimization of thermal performance of packed bed latent heat thermal storage system based on response surface method," Renewable Energy, Elsevier, vol. 153(C), pages 669-680.
    • Handle: RePEc:eee:renene:v:153:y:2020:i:c:p:669-680
    DOI: 10.1016/j.renene.2020.01.157
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