Air conditioning systems account for a large proportion of primary energy consumption for providing a healthy and thermally comfortable indoor environment. Air distribution is the connection between the indoor environment and the air conditioning system, thereby significantly affecting the indoor environment quality and the system energy efficiency. Compared with the conventional uniform air distribution (i.e., mixing ventilation), non-uniform air distribution (e.g., stratum ventilation and displacement ventilation) is recognized to improve the energy efficiency of the air conditioning system effectively for thermal comfort and indoor air quality. To leverage the advantages of non-uniform air distribution, a paradigm shift from uniform air distribution to non-uniform air distribution is getting more and more attention. Recent studies mainly focus on technological feasibilities and design issues of non-uniform air distribution. However, when operating non-uniform air distribution, a dissatisfied indoor environment and unnecessary energy use would occur, because the recent practice ignores or oversimplifies the effects of the non-uniformity of air distribution on indoor environment quality and system energy efficiency. Thus, a proper operation strategy oriented for non-uniform air distribution should be proposed to facilitate the paradigm shift from uniform air distribution to non-uniform air distribution.

This thesis proposes a coupled operation optimization of the non-uniform air distribution and air conditioning system, which satisfies occupants’ demands on the indoor environment quality and minimizes system energy consumption simultaneously. The proposed coupled operation optimization mainly includes two parts. The first part is to model non-uniform air distribution efficiently. The information on non-uniform air distribution is indispensable for the operation. Direct measurements of non-uniform air distribution would result in a large cost of the sensors and occupant-unfriendly invasions by the sensors, while CFD simulations of non-uniform air distribution are computationally impractical. In this thesis, computationally efficient models of non-uniform air distribution are developed. An empirical model of heat removal effectiveness (representing the air distribution characteristic) is first established. Based on the heat removal effectiveness, a multi-node model is developed to describe the non-uniform indoor thermal environment. Based on the multi-node model, non-uniformity-to-uniformity suggoration methodology is proposed to enable the existing building energy simulation tools with the model of the uniform air distribution (i.e., fully mixed air model) to accurately evaluate the energy performance of the air conditioning system with non-uniform air distribution. The proposed efficient modelling methods are experimentally validated to be accurate and robust for the two representatives of non-uniform air distribution, i.e., stratum ventilation and displacement ventilation.

With the developed models in the first part, the second part of this thesis proposes a coupled operation optimization of the non-uniform air distribution and air conditioning system. The proposed coupled operation optimization firstly identifies the alternative operations meeting the occupants’ demands on thermal comfort and indoor air quality, and secondly determines the optimal operation with the maximal energy efficiency from the identified alternative ones. More specially, for the scenario with user-defined demands on thermal comfort, a supervisor control optimization on the room air temperature is proposed. The thermal comfort model in ASHRAE 55 is modified to be a function of the room air temperature and supply airflow rate, which can take into account the elevated room air velocity for thermal comfort and energy saving. Based on the modified thermal comfort model, the optimal room air temperature is determined for the maximal energy saving with the demanded thermal comfort. To track the optimal room air temperature under the dynamic condition, a local control method of the room air temperature is also proposed. For the scenario with user-defined demands on indoor air quality, a supervisory control optimization on the fresh outdoor air ratio is proposed. The model of CO2 concentration in the breathing zone is developed by coupling the CO2 removal efficiency and mass conservation law, which is used to indicate the inhaled air quality. Based on the model of CO2 concentration in the breathing zone, the fresh outdoor air ratio is optimized for the maximal energy saving with quality inhaled air. Validation case studies in a stratum ventilated classroom and office show that the conventional operation strategies cause thermal discomfort and poor inhaled air quality. The proposed operation optimization exactly meets the occupants’ demands on thermal comfort and inhaled air quality, and further harvests energy saving up to 67%. The proposed coupled operation optimization is also promising for air conditioning systems with other modes of air distribution.

The proposed coupled operation optimization is essentially an innovative demand-controlled ventilation method. The existing demand-controlled ventilation method harvests energy saving from the variations of occupancy number. However, when the occupancy number is fixed, the existing demand-controlled ventilation method can save no more energy. In contrast, the innovative demand-controlled ventilation method can further harvest energy saving by optimizing air distribution with the fixed occupancy number. This provides a new opportunity for energy saving of the air conditioning system while satisfying the occupants’ demands on thermal comfort and indoor air quality. Moreover, since the proposed coupled operation optimization is based on the efficiently models of non-uniform air distribution, it can be implemented conveniently in practice. Therefore, the proposed coupled operation optimization by this thesis could help to prompt the paradigm shift from uniform air distribution to non-uniform air distribution for the sustainable development of the building sector.