Diverse occupant behaviors and energy conservation opportunities for university student residences in Hong Kong

Occupant behavior significantly influences building energy consumption. However, two research gaps exist, namely, the lack of firsthand data for a complete understanding of the complex and stochastic nature of occupant behavior, and the limited consideration given to socio-psychological factors in the classification of behavior modes. This study aims to expand on the existing database of occupant behavior and propose an interdisciplinary classification framework of behavior modes. First, a hierarchy of behavior modes was developed considering occupants’ demand for comfort, preference for certain behavior, and energy dependence. Occupants were classified as “Active, Moderate, and Cautious” energy users. Then, the proposed “AMC” hierarchy was verified via a case study using a high-rise student residence in Hong Kong. Mixed methods were applied, including a questionnaire survey of 137 students, in-situ monitoring of adaptive behaviors using noninvasive sensors in 12 rooms, building energy simulation validated by full-season metered energy use data, and scenario analysis considering multifaceted factors. The results show that, interestingly, observable discrepancy of behavior patterns exists even among users of the same sort. Also, five key influencing factors, i.e. room orientation, floor, schedule, room temperature settings, and behavior modes of active, moderate and cautious users, explain 79% of the difference in cooling energy consumption, among which behavior modes induce the largest contribution. In addition, technical and socio-psychological barriers impede energy saving of active and moderate users. Although behavior changes may conserve up to 45% of cooling energy consumption, skillful selection of appropriate interventions is necessary in order to fulfill the expectancy. •A three-level hierarchy has been proposed to identify typical energy behavior modes.•Technical and socio-psychological boundaries impede the energy saving of active and moderate users.•Five key influencing factors explain the different cooling energy consumption of 79% users.•Behavior patterns are largely distinguished between users with different behavior modes.•Behavior change will help achieve up to 45% energy savings in air conditioning in HK climate.