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

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 multiobjective 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.

Automated summary

The study focuses on the analysis and optimization of packed bed thermal energy storage, evaluating the influence of quasi-dynamic boundary conditions on its performance. Additionally, a complete methodology for designing packed bed thermal energy storage is proposed.