Developing a new adaptive heat balance model to enhance thermal comfort predictions and reduce energy consumption

Accurate thermal comfort prediction is essential for enhancing both thermal comfort and energy efficiency in buildings. The heat balance and adaptive models, while widely used, have been often questioned in relation to their strengths and limitations. To overcome these challenges, a comprehensive understanding of both the physical parameters influencing heat exchange and occupants' adaptive capacities is essential. This study introduces an analytical method to formulate a new adaptive heat balance model, the adPMV, which integrates the strengths of both models considering various parameters influencing thermal perception. The model integrates the PMV with an adaptive factor associated with the running mean outdoor temperature, in line with adaptive theory. Tested on 1377 samples from European university classrooms, the adPMV demonstrates enhanced accuracy (MAE=0.74, RMSE=1.01, MBE=-0.11) compared to PMV and other adaptive heat balance models. Validation on naturally ventilated university classrooms from ASHRAE's databases further confirms promising results, showcasing reduced error indices (MAE=0.68, RMSE=0.81, MBE=-0.03). Notably, using adPMV setpoints not only improves thermal sensation prediction accuracy but also leads to a substantial reduction in heating demand, reaching up to 40 %. The adaptability of this model to different contexts, such as building types, climates, and HVAC system operations, presents it as a versatile tool for exploring adaptive principles.