LAUSR

Thermal energy capacity of buildings can be coupled to power networks via heating, ventilating, and air-conditioning (HVAC) units. Optimizing the operation of HVAC systems in multizone buildings is a challenging task, as occupants have different thermal preferences dependent on time-varying indoor and outdoor environments. To estimate the social cost of demand response (DR), building aggregators need to assess occupants’ thermal discomfort (TD), which is related to their productivity outcomes. This paper proposes a price-based DR strategy for multizone office buildings to co-optimize the energy cost of HVAC units and the TD levels of occupants. To overcome simplified TD representations, a mobile interface is developed that grants occupants the ability to indicate their personal thermal preferences. These preferences are modeled using artificial neural networks, which are explicitly and directly integrated into the optimal DR scheduling. In addition, we evaluate the thermal response of a multizone office building to the operation of a variable speed heat pump (VSHP). Using the models of occupants’ TD and building thermal response, the optimization problem for the proposed DR strategy is formulated and solved with mixed-integer linear programming. The case study results verify that the proposed strategy successfully optimizes VSHP operations and occupants’ TD levels, mitigating the risk of occupant interruption to the optimal DR schedule.