Boundary conditions for energy storage

Which boundary conditions should be considered when optimizing thermal energy storage?

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.

Do boundary conditions affect thermal energy storage performance?

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.

Do quasi-dynamic boundary conditions affect storage thermal efficiency?

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.

How can packed bed thermal energy storage be optimized?

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.

How can energy storage allocation be more secure and reliable?

Subsequently, a more secure and reliable energy storage allocation model is constructed by taking into account the boundary conditions of energy storage charging and discharging efficiency, energy balance, state of charge, and target power output fluctuation.

Is a packed bed thermal energy storage a viable energy storage solution?

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.