Improving Indoor Thermal Comfort and Air-Conditioning Management in Representative Primary Schools in Southern China

This study aims to optimize indoor thermal environment assessment methods for primary school classrooms in regions with hot summers and cold winters, enhancing air-conditioning management efficiency and accuracy. Given the complexity of Predicted Mean Vote (PMV) calculations and its reduced accuracy under high temperature and humidity, this research explores the use of Thermal Sensation Vote (TSV) as a simpler alternative. Field measurements and subjective assessments were conducted to analyze the relationship between TSV and PMV, leading to a regression model linking predicted TSV (TSV_p) with temperature and humidity. Results indicate that temperature and humidity significantly impact TSV, with regression coefficients of 0.499 and 0.055, respectively. Furthermore, when TSV is ≥1, the proportion of PMV of ≥0.5 remains stable, validating TSV_p as a reliable indicator. Based on these findings, energy-efficient air-conditioning management strategies are proposed, recommending a temperature setting of 28 °C for thermal comfort. This study provides insights into climate control strategies in educational buildings, promoting sustainable development.