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As one of the latest emerging HVAC technologies, the Variable Refrigerant Flow (VRF) system with heat recovery (HR) configurations has obtained extensive attention from both the academia and industry. Compared with the conventional VRF systems with heat pump (HP) configurations, VRF-HR is capable of recovering heat from cooling zones to heating zones and providing simultaneous cooling and heating operations. This can further lead to substantial energy saving potential and more flexible zonal control. In this paper, a novel model is developed to simulate the energy performance of VRF-HR systems. It adheres to a more physics-based development with the ability to simulate the refrigerant loop performance and consider the dynamics of more operational parameters, which is essential for representing more advanced control logics. Another key feature of the model is the introduction of component-level curves for indoor units and outdoor units instead of overall performance curves for the entire system, and thus it requires much fewer user-specified performance curves as model inputs. The validation study shows good agreements between the simulated energy use from the new VRF-HR model and the laboratory measurement data across all operational modes at sub-hourly time steps. The model has been adopted in the official release of the EnergyPlus simulation program since Version 8.6, which enables more accurate and robust assessments of VRF-HR systems to support their applications in energy retrofit of existing buildings or design of zero-net-energy buildings. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]