Dynamic optimization based integrated operation strategy design for passive cooling ventilation and active building air conditioning

As one form of passive cooling, night ventilation (NV) has been proven effective to improve the building energy performance. In previous studies, however, fixed NV operating strategies were usually pre-defined, ignoring the weather condition variations over the whole operation process, the influence of outdoor humidity on NV's efficiency, and NV's integrated performance with active air conditioning systems. Such strategies may have potentials for further improvements. This paper presents a systematic approach to address the dynamic optimization of integrated operation of NV and active building air conditioning using typical variable-air-volume (VAV) systems as the case. In the optimization scheme, the physical model is developed per differential algebraic equations (DAEs). The simultaneous collocation method is introduced to translate the dynamic optimization into a nonlinear program, which is then implemented in the GAMS platform and handled by IPOPT solver. The study results indicate that the optimized strategies lead to a remarkable energy saving of 23.19-49.31% in different climate conditions compared to the traditional local control scheme without NV, and a saving of 14.97-39.70% compared to that with pre-defined NV.