Determining optimal thermal energy storage charging temperature for cooling using integrated building and coil modeling

摘要

Thermal energy storage (TES) systems coupled with heat pumps offer significant potential for improving building energy efficiency by shifting electricity demand to off-peak hours. However, conventional operating strategies maintain conservatively low chilled water temperatures throughout the cooling season, a practice that results in suboptimal heat pump performance. This study proposes a physics-based integrated simulation framework to determine the maximum feasible chilled water supply temperature while ensuring cooling stability. The framework integrates four submodels: relative humidity prediction, dynamic cooling load estimation, cooling coil performance prediction, and TES discharge temperature prediction. Validation against measured data from an office building demonstrates reliable accuracy across all sub-models (e.g., CVRMSE of 9.3% for cooling load and R2 of 0.91 for peak-time discharge temperature). The integrated simulation reveals that the proposed framework can increase the daily initial TES charging temperature by an average of 2.55 °C compared to conventional fixed-temperature operation, enabling the heat pump to operate at a higher coefficient of performance. This study contributes a practical methodology for optimizing TES charging temperatures in building heating, ventilation, and air conditioning (HVAC) systems while maintaining indoor setpoint temperatures.