An Occupant-participatory Approach for Thermal Comfort Enhancement and Energy Conservation in Buildings

CIS Seminar

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.