Thermal Comfort in Intelligent Buildings—The Impact of the CO2 Level on Thermal Sensations and the Development of a Modified Thermal Comfort Model

Providing comfortable environmental conditions in buildings requires energy. Thermal comfort depends on many factors, and successful prediction of thermal sensations based on physical parameters of indoor environment is a challenge. However, the issue is of significant importance because HVAC (heating, ventilation, air conditioning) systems consume considerable thermal and electrical energy and should be operated most efficiently to reduce energy needs while maintaining thermal comfort conditions. It is especially vital in intelligent buildings whose systems and services are large energy consumers. In this paper, a modified thermal comfort model (based on the large-scale questionnaire study conducted on intelligent buildings) is developed. It considers the impact of carbon dioxide, which was observed to be associated with higher thermal sensations with rising CO2 levels. The modification was based on the Box–Behnken method, which has never been performed in such studies. Modified correlations for PMV and PPD indexes proved more accurate than in the original model. Moreover, implications of the modification of this model with regard to energy consumption are discussed; however, this issue proved to be quite complicated as it involves not only input data of the physical indoor parameters but also subjective preferences of the respondents.