Design optimization of an innovative layered radial-flow high-temperature packed bed thermal energy storage

JOURNAL OF ENERGY STORAGE(2024)

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摘要
The present work introduces an innovative layered radial flow packed-bed thermal energy storage able to provide enhanced thermal and hydrostatic performance, limiting their inherent trade-off. The performance of the proposed packed-bed thermal energy storage concept is modelled, in both thermal and hydrodynamic aspects, via a 1D-two phases numerical approach. Representative storage sizes for industrial applications and laboratory prototype are considered to highlight the potential for scaling and the representativeness of prototyping. Configurations with two and three coaxial layers are also analyzed. The investigation includes a multi-objective optimization of the thermal energy storage design considering a set of main design variables and a set of sensitivity analyses aimed at highlighting the influence of major operational parameters. The results show that the proposed storage geometry can provide simultaneous optimization of both thermal and hydrodynamic performance. The proposed storage unit could attain pressure drop reductions higher than 70 % with respect to uniform radial flow packed bed storage (and higher than 85 % with respect to axial flow units) at the expense of a useful duration reduction lower than 5 %. Industrial scale storage would benefit from low aspect ratios and arrangement with modular units, ensuring enhanced system flexibility and reduced parasitic consumptions thanks to lower pressure losses meanwhile guaranteeing extensive useful durations in both charge and discharge operation. Downscaled prototypes can provide a good representation of the thermal and hydrodynamic behavior of the proposed thermal energy storage solution and a relevant base for validation. This work paves the way for future prototyping and validation of the proposed layered radial flow packed-bed thermal energy storage concept.
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关键词
Thermal energy storage,Packed bed,Design multi-objective optimization,High temperature
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