Thermal preference-based control studies: review and detailed classification

Abstract

In the last few years, a significant amount of research has focused on learning and modeling personalized thermal preferences to satisfy individuals in buildings. However, there is a disconnection between personal comfort studies and building thermal control research. The objective of this article is to review research studies that integrate personalized thermal preferences into building control systems, and their control performance (in terms of comfort and energy) through either simulation studies or field implementations. Existing studies can be categorized into two main categories, depending on the type of control integration: conventional, reactive (feedback) control and advanced model-based predictive control. A deeper analysis of the degree of integration, number of occupants considered, control setpoint type, and thermal preference aggregation method, leads to a more detailed classification of thermal preference-based control research. In the absence of a general consensus of robust implementation of thermal preference-based control in buildings, this categorization allows a better understanding of current focus, research gaps, and needs for future work.