Personalized Thermal Comfort Driven Control in HVAC Operated Office Buildings

Occupant comfort is a dominant influence on the performance of HVAC operations. Most HVAC system operations rely on industry standards to ensure satisfactory environmental conditions during occupancy. Despite the increasing building energy consumption rates, occupants are not usually satisfied with indoor conditions in commercial buildings. To address this issue, in this paper, a framework for integrating personalized comfort preferences into HVAC control logic is introduced. As part of the framework, a user proxy, a comfort profile learning algorithm, and a building management system (BMS) controller are presented. The performance of the framework in a real building setting has been evaluated. The framework was successful in a small-scale experiment in increasing efficiency by improving user comfort and slight decrease in collective energy consumption.