Most existing models for greenhouse cooling energy prediction assume static boundary conditions, neglecting airflow speed dynamics. This simplification overlooks the influence of airflow on aerodynamic resistance, which governs crop transpiration and leaf-to-air heat transfer, potentially causing large prediction errors. In this study, a greenhouse building energy simulation model was developed to incorporate crop heat exchange dynamics influenced by airflow speed. A set of airflow speed profiles derived from computational fluid dynamics simulation was used to quantify cooling energy behavior and uncertainty across airflow speed cases. The results revealed that cooling energy decreased with increasing airflow speed, yet the reduction became progressively less substantial at higher airflow speed. The maximum difference in total cooling energy across airflow speed cases reached 57.4%, indicating substantial modeling uncertainty. This is because transpiration and leaf-to-air heat transfer increased as aerodynamic resistance decreased. In addition, the daily standard deviation of cooling energy across airflow speed groups peaked at 1,264.88 kWh in August, more than twice that of June and September, highlighting amplified uncertainty in July and August due to higher outdoor temperatures and daily energy fluctuations. This study deepens the understanding of the dynamics of crop heat exchange according to the airflow speed and lays the groundwork for providing more accurate prediction models.
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