LAUSR

Abstract Model-based optimization can help improve the indoor thermal comfort and energy efficiency of Heating, Ventilation and Air Conditioning (HVAC) systems. The models used in previous optimization studies either omit the dynamic interaction between indoor airflow and HVAC or are too slow for model-based optimization. To address this limitation, we propose an optimization methodology using coupled simulation of the airflow and HVAC that captures the dynamics of both systems. We implement an optimization platform using the coupled models of a coarse grid Fast Fluid Dynamics model for indoor airflow and Modelica models for HVAC which is linked to the GenOpt optimization engine. Then, we demonstrate the new optimization platform by studying the optimal thermostat placement in a typical office room with a VAV terminal box in the design phase. After validating the model, we perform an optimization study, in which the VAV terminal box is dynamically controlled, and find that our optimization platform can determine the optimal location of thermostat to achieve either best thermal comfort or least energy consumption, or the combined. Finally, the time cost for performing such optimization study is about 6.2 h, which is acceptable in the design phase.