Packed bed thermal energy storage: A novel design methodology including quasi-dynamic boundary conditions and techno-economic optimization. (April 2021)

• Record Type: Journal Article
• Authors: Trevisan, Silvia; Jemmal, Yousra; Guedez, Rafael; Laumert, Björn
• Is Part Of: Journal of energy storage. Volume 36(2021)
• Publication Date: 2021-04
• Subjects: Packed bed -- Thermal energy storage -- Design methodology -- Levelized cost of storage -- Multi-objective optimization; Energy storage -- Periodicals; Energy storage -- Research -- Periodicals; 621.3126
• DOI: 10.1016/j.est.2021.102441
• Languages: English
• ISSNs: 2352-152X

Abstract

Highlights: A novel design methodology for packed bed TES is proposed. Quasi-dynamic boundary conditions worsen the TES performance. Quasi-dynamic boundary conditions reduce of 5% the TES thermal efficiency. Similar TES designs can minimize the LCoS independently on the boundary conditions. The LCoS can be used as a more reliable indicator for packed bed TES optimization. Abstract: High temperature thermal energy storages are becoming more and more important as a key component in concentrating solar power plants. Packed bed storages represent an economically viable large scale energy storage solution. The present work deals with the analysis and optimization of a packed bed thermal energy storage. The influence of quasi-dynamic boundary conditions on the storage thermodynamic performance is evaluated. The Levelized Cost of Storage is innovatively applied to thermal energy storage design. A complete methodology to design packed bed thermal energy storage is proposed. In doing so, a comprehensive multi-objective optimization of an industrial scale packed bed is performed. The results show that quasi-dynamic boundary conditions lead to a reduction of around 5% of the storage thermal efficiency. Contrarily, the effect of the investigated design variables over the TES LCoS optimization is only slightly influenced by quasi-dynamic boundary conditions. Aspect ratio between 0.75 and 0.9 would maximize the storage thermal efficiency, while low preliminary efficiency around 0.47 would minimize the Levelized Cost of Storage. This work testifies that quasi-dynamic boundary conditions should be taken into considerations when optimizing thermal energy storage. The Levelized Cost of Storage could be also considered as a more reliable performance indicator for packed bed thermal energy storage, as it is less dependent on variable boundary conditions.