Investigating the relationship between predicted and perceived thermal comfort conditions in an educational building

Thermal comfort is one of the most important factors affecting the health of users, work efficiency and productivity in indoor environments and it significantly affects attention, perception and learning levels of students in educational buildings. Today, building systems are operated according to predefined setpoints, which are set according to standards with predefined comfort intervals for all climate zones. However, thermal sensation, preference and acceptability of users can vary according to different climatic conditions. In this thesis, indoor environmental conditions were recorded during heating and cooling periods in an educational building and Predicted Mean Vote (PMV) indices were calculated. In addition, Actual Mean Vote (AMV) indices were obtained via questionnaires and compared to PMV indices via statistical analyses. The results show that the PMV model cannot predict students' thermal comfort perceptions during the heating period and there is a positive and strong correlation between PMV and AMV indices. In addition, users who live in hot climates may have a higher likelihood of choosing cooler environmental conditions even during the heating period.