Indoor thermal environment optimal control for thermal comfort and energy saving based on online monitoring of thermal sensation

Abstract

The automatic control of Heating, ventilation and Air Conditioning (HVAC) systems aims to achieve the thermal comfort requirements of occupants with minimum energy consumption. The automatic control strategy of existing HVAC systems determines a set value for creating a thermal environment in accordance with relevant design principles and/or occupants’ preferences. An overly-cooled indoor environment may reduce the occupant's thermal comfort and result in excessive energy consumption. In order to improve thermal comfort and save energy, this study proposes an indoor thermal environment optimal control method based on the online monitoring of thermal sensation. First, a smart wristband collects the human physiological data, including wrist skin temperature and heart rate. This is for predicting human thermal sensation, where a fuzzy comprehensive evaluation method is employed to determine the integrated thermal sensation of multi occupants. Then, a linear adjustment algorithm is developed to optimize the indoor temperature set point. In order to evaluate the performance of the thermal sensation-based control method, a series of experiments were conducted using the thermal sensation-based control and set point-based control. The results show that the thermal sensation-based control can adjust the temperature setting in a timely fashion according to the occupants’ integrated thermal sensations, although they do not necessarily state their subjective perception. It is also revealed that the thermal sensation-based control can achieve a more comfortable thermal environment than the set point-based control. Furthermore, the thermal sensation-based control saves 13.8% in daily energy consumption compared to the set point-based control method.