Heat transfer of a large-scale water pit heat storage under transient operations

An accurate and less time demanding model is required when integrating pit thermal energy storage (PTES) into solar heating systems. Multi-node (1D) models are commonly used, but these models face challenges when calculating PTES thermal stratification and heat loss. Therefore, a full-scale computational fluid dynamics (CFD) model of PTES inclusive water and soil regions is developed using FLUENT to improve the accuracy of heat transfer calculation of a multi-node model. The CFD model is validated against the Dronninglund PTES mea-surements regarding PTES thermal stratification, inlet/outlet energy flow, and soil temperature distribution. The model corresponds well to the measurements in three aspects: (i) a maximum temperature difference of 1 K in the water region; (ii) a maximum temperature difference of 2 K in the soil region; (iii) a maximum outlet temperature difference of 3 K. An indicator R & UDelta;T/delta defined as the ratio between the thermocline temperature difference and the thermocline thickness is proposed to assess suitable grid size for PTES models, and the quantitative relationship between R-delta T/delta and grid size is recommended. Investigations with a range of grid sizes show that by using the recommended grid size, the prediction accuracy of the multi-node model TRNSYS Type 343 is significantly improved. The root mean square deviations of the predicted MIX number are decreased by 11-43 % for different years, and the relative differences of the monthly charge/discharge energy from the measurement are within 5 %. The findings of this study provide guidance for selecting appropriate grid sizes to achieve better calculation accuracy for large-scale PTES.

Automated summary

This study presents a full-scale computational fluid dynamics model of PTES that includes water and soil regions, aiming to improve the accuracy of heat transfer calculation in multi-node models. The model is validated against measurements and shows good agreement in thermal stratification, energy flow, and soil temperature distribution.