Online HVAC-aware occupancy scheduling with adaptive temperature control

Abstract

Heating, ventilation and air-conditioning (HVAC) is the largest consumer of electricity in commercial buildings. Consumption is impacted by group activities (e.g. meetings, lectures) and can be reduced by scheduling these activities at times and locations that minimize HVAC utilization. However, this needs to preserve occupants’ thermal comfort and be responsive to dynamic information such as new activity requests and weather updates. This paper presents an online HVAC-aware occupancy scheduling approach which models and solves a joint HVAC control and occupancy scheduling problem. Our online algorithm greedily commits to the best schedule for the latest activity requests and notifies the occupants immediately, but revises the entire future HVAC control strategy each time it considers new requests and weather updates. In our experiments, the quality of the solution obtained by this approach is within 1% of that of the clairvoyant solution. We incorporate adaptive comfort temperature control into our model, encouraging energy saving behaviors by allowing the occupants to indicate their thermal comfort flexibility. In our experiments, the integration of adaptive temperature control further generates up to 12% of energy savings when a reasonable thermal comfort flexibility is provided.