Abstract
The personal comfort system (PCS) aims to meet individual thermal comfort demands efficiently to achieve higher thermal comfort satisfaction while reducing air conditioning energy consumption. To date, many PCS devices have been developed and evaluated from the perspective of thermal comfort. It will be useful for future PCS development if an approach to quantify the thermal comfort and energy performance of certain PCS devices and their combinations with consideration of user behaviors can be established. This study attempted to fill this gap by integrating thermal comfort experiments, occupancy simulations, usage behavior modeling, and building energy simulation technologies. First, human subject experiments were conducted to quantify the thermal comfort effects of the PCS. Then, the Markov chain model and conditional probability model were employed to describe the room occupancy and PCS usage behaviors. Finally, the extended comfort temperature range and user behavior models were imported into the building energy simulation tool to analyze the energy-saving potential of the PCS. The results show that the use of PCS can significantly improve occupants' thermal comfort and satisfaction rate under both warm and cool conditions. Using a cooling cushion and desktop fan can lift the upper limit of the comfortable temperature to 29.5 ℃ while the heated cushion can extend the lower limit to 15 ℃. By increasing the air conditioning temperature setpoint by 2 ℃ in summer and reducing by 2.5 ℃ the heating temperature setpoint in winter, PCS devices can reduce heating and air conditioning energy consumption by 25%–40% while maintaining occupants' thermal comfort.
