Skip to main navigation Skip to search Skip to main content

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

  • CAS - Institute of Electrical Engineering

Research output: Contribution to journalJournal articleResearchpeer-review

25 Downloads (Orbit)

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.

Original languageEnglish
Article number120191
JournalRenewable Energy
Volume224
Number of pages15
ISSN0960-1481
DOIs
Publication statusPublished - 2024

Keywords

  • Multiple linear regression model
  • Multiple phase change materials
  • Packed bed
  • Thermal energy storage

Fingerprint

Dive into the research topics of 'Identifying driving factors in cascaded packed bed latent thermal energy storage: An experimental validation'. Together they form a unique fingerprint.

Cite this