A knowledge based approach for selecting energy-aware and comfort-driven HVAC temperature set points

HVAC systems are responsible for providing acceptable thermal conditions and indoor air quality for building occupants. Increasing thermal comfort and reducing HVAC related energy consumption are often seen as conflicting goals. Few researchers have investigated the feasibility of reducing HVAC related energy consumption by integrating occupants' personalized thermal comfort preferences into the HVAC control logic. In this study, we introduce a knowledge-based approach for improving HVAC system operations through coupling personalized thermal comfort preferences and energy consumption patterns. In our approach, thermal comfort preferences are learned online and then modeled as zone level personalized comfort profiles. Zone temperature set points are then selected through solving an optimization problem for energy, with comfort, indoor air quality, and system performance constraints taken into consideration. In the case that acceptable comfort levels for all occupants of a zone were not achievable, the approach selects set points that minimize the overall thermal discomfort level. Compared to an operational strategy focusing on comfort only, evaluation of our approach, which aims for both maintaining or improving comfort and reducing energy consumption, showed improvements by reducing average daily airflows for about 57.6 m3/h (12.08%) in three target zones.