JOURNAL ARTICLE

Performance analysis of solar thermal storage systems with packed bed utilizing form-stable phase change materials and heat pump integration.

  • Published In: Journal of Renewable & Sustainable Energy, 2024, v. 16, n. 3. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Wang, Changling; Gao, Yuanzhi; Yang, Juan; Liu, Baobin; Dai, Zhaofeng; Wu, DongXu; Xia, Yujiang; Yu, Jing; Yan, Weidong; Zhang, Xiaosong 3 of 3

Abstract

This article focuses on the development and numerical analysis of a solar thermal energy storage system using a phase change material (PCM) packed bed coupled with a heat pump. The study evaluates the thermal storage and heat extraction performance under varying solar irradiation intensities, opening times, heat collection areas, PCM compositions (paraffin content and graphene nanoparticle addition), and packed bed porosities. Results indicate that higher solar irradiance and optimal operation times (9:00 a.m. or 11:00 a.m.) enhance storage efficiency, while increased paraffin content prolongs phase change duration and nanoparticle addition slightly reduces it. Lower porosity beds yield more uniform temperature distribution but higher pressure drops, and coupling with a heat pump demonstrates adaptable heat extraction rates, maintaining stable outlet temperatures over varying durations. These findings contribute to optimizing solar thermal storage integrated with heat pumps for improved energy efficiency and stability in renewable energy applications.

Additional Information

  • Source:Journal of Renewable & Sustainable Energy. 2024/05, Vol. 16, Issue 3, p1
  • Document Type:Article
  • Subject Area:Power and Energy
  • Publication Date:2024
  • ISSN:1941-7012
  • DOI:10.1063/5.0206364
  • Accession Number:178147786
  • Copyright Statement:Copyright of Journal of Renewable & Sustainable Energy is the property of American Institute of Physics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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