An Occupant-participatory Approach for Thermal Comfort Enhancement and Energy Conservation in Buildings
Time: Thur Nov 6, 11:00AM-12:00PM Place: Anderson Room 21 Title: An Occupant-participatory Approach for Thermal Comfort Enhancement and Energy Conservation in Buildings Abstract: Commercial building is one of the major energy consumers worldwide. Among the building services, the heating, ventilating and air-conditioning (HVAC) system dominates the total energy consumption; hence recent studies proposed many approaches to audit, automate and optimize energy usage of HVAC systems. Nevertheless, these schemes seldom discuss human thermal comfort. To minimize complaints, the current practice by facility management is to use very conservative temperatures, leading to large energy waste. We thus propose to actively take thermal comfort into consideration. We propose a participatory approach where the occupants can provide feedback on their comfort levels. A major challenge for a participatory design is to reduce intrusiveness of the system. To this end, we develop a temperature-comfort correlation model which can build a profile for each occupant; thus the building air-conditioning adjustment decision can be primarily model-driven and only needs minimal inputs from the occupants. We validate our model with field experiments. We also implement a system and conduct field experiments in a University and a commercial office environment. We show that our algorithm can successfully maintain high thermal comfort, while reducing energy consumption for 18%. Bio: Dan Wang received his B. Sc from Peking University, Beijing, M. Sc from Case Western Reserve University, Cleveland, OH, and Ph. D. from Simon Fraser University, Vancouver, Canada, all in Computer Science. He is an Associate Professor of Department of Computing, The Hong Kong Polytechnic University, Hong Kong. His recent research interest includes Green Computing, Big Data Computing, etc. He is a senior member of the IEEE.