Identifying driving factors in cascaded packed bed latent thermal energy storage: An experimental validation

Jiani Wu, Jianhua Fan, Tianzeng Ma, Weiqiang Kong, Zheshao Chang and Xin Li

Renewable Energy, 2024, vol. 224, issue C

Abstract: The cascaded packed bed latent thermal energy storage (PBLTES) system, an innovative and efficient technique, remains unexplored experimentally in terms of driving factors and cyclic stability. To address this gap, this study designed a cascaded PBLTES system, employing three phase-change-materials with varied phase transition temperatures. Parametric experiments were conducted to measure phase transition in capsules and temperature changes in heat transfer fluid. Pearson's correlation coefficients were used to establish relationships between driving factors and thermal performance metrics. This study developed multiple linear regression models based on experimental correlations to evaluate and predict thermal performance under various conditions. These results indicated that the employed multiple regression models are capable of making reliable quantitative predictions regarding the thermal behavior of cascaded PBLTES systems. The models showed a good fit to the experiment data (lowest R2 value at 0.776). The results also showed that the flow rate significantly affected total and phase transition times of the cascaded PBLTES for charging/discharging, with substantial Standardized Linear Regression Coefficients of −0.79/-0.8 and −0.74/-0.72, respectively. In contrast, inlet temperature, with coefficients of −0.18/0.15 and −0.34/0.21, has about a quarter of the flow rate's impact. These findings provide compelling experimental substantiation for the design of cascaded PBLTES.

Keywords: Packed bed; Multiple phase change materials; Thermal energy storage; Multiple linear regression model (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:224:y:2024:i:c:s0960148124002568

DOI: 10.1016/j.renene.2024.120191

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