Research On The VRF And VAV Combined Air Conditioning System And Its Coordinated Optimization Control Method

Multi-split VRF system has been widely applied in middle and small buildings due to good part load performance and individual thermal comfort. However, the shortcomings restrict its wider applications. Specially, the problem of the VRF system in outdoor air ventilation has not been solved thoroughly, which arouses more attentions nowadays as people are aware of the importance of ventilation to the indoor air quality. Further, simulation and optimization of the VRF system and its combination with buildings are not well studied. It will benefit much to solve these problems with the state-of-the-art theories and techniques. In light of the current situation, a VRF and VAV combined air conditioning system is carefully studied. Models from components to the whole system are developed, and coordinated optimization control strategies from local to global levels are proposed.Firstly, after the design of the combined system, generic simulation models of the VRF system are modeled and validated using experimental data. The developed VRF system models, including cooling mode and heating mode, are characterized by component number independence. So they are suitable for simulation of both the outdoor air processing(OAP) unit in VAV part and the VRF unit. With an insight into the varying rules of the parameters of the system, an iterative algorithm is proposed to accelerate the calculation. The iterations for the superheated degree can be decreased to only 2 times, which greatly enhances the applicability of the simulation models. Besides, explicit calculation models for the refrigerant properties are also developed by curve-fitting method. The discontinuity of the properties and the reproducibility of enthalpy-temperature calculation in superheated and sub-cooled regions are improved greatly using a new correction method. An experimental rig is developed to validate the VRF models in both steady state and dynamic conditions. Results show the developed models are feasible for further energy and control analysis of the VRF system.Secondly, a dynamic simulator of the combined system is developed based on VRF and other components’ models and operation performances of the combined system are analyzed. It is found that the combined system could maintain all the zones at their specific set-points within small errors no matter the set-points are the same or not. The individual control of the thermal comfort can be satisfied. Ventilation problem of the VRF system is well solved and the indoor air quality can be ensured. It is also found that the changing outdoor air supply temperature leads to a reciprocal relationship of cooling capacity between the VRF unit and the OAP unit, which opens up an opportunity to minimize the energy consumption of the combined system by optimizing the outdoor air supply temperature. Further research finds that the optimized outdoor air supply temperature results in part load ratio of the units locate in a range(0.4~0.7) that the units have the highest efficiency.Following, two outdoor air supply temperature oriented operation parameter optimization methods are proposed. The first method searches the best load distribution between the VRF unit and the OAP unit. The optimized outdoor air supply temperature then is transformed from the load distribution result. The second method combines models with artificial intelligence. Online adaptive simplified models are developed to predict performances of the combined system. The optimized outdoor air supply temperature is directly searched using intelligent algorithm(genetic algorithm). Tests show that both of the two control methods can effectively decrease energy consumption of the combined system compared to conventional control strategies.Finally, a global coordinated optimization control method is proposed for effective operation of the combined system in whole-year working conditions. The two outdoor air supply temperature optimal control methods are called local coordinated optimization control method since they have a pre-condition that both the VRF unit and the OAP unit should be operating. However, when one of the units operates with low energy efficiency, the system energy efficiency will not be that high even if the local coordinated optimization control method is applied. The global coordinated optimization control method is a development of the local one. In the global method, the unit which operates at low energy efficiency can be stopped. When the load increases up to certain threshold, the stopped unit then is restarted to take advantages of the local coordinated optimization control method again. Doing this, the combined system will operate with high energy efficiency in the whole-year working conditions. Tests show the global coordinated optimization control method can effectively decrease the energy consumption of the combined system compared to other control strategies, including the local one. The global coordinated optimization control method provides a feasible solution of energy conservation of the combined system. All these work lay solid foundations for effective operation and energy management of the studied combined system.