Control and Optimization of Dedicated Outdoor Air-Chilled Ceiling Systems Using Liquid Desiccant Dehumidification

In the research, a dedicated outdoor air-chilled ceiling (DOAS-CC) system adopting a novel membrane-based total heat exchanger and liquid desiccant dehumidification is proposed and studied. It can achieve independent indoor temperature and humidity controls, provide more effective ventilation, prevent bacteria transmission among different zones, reduce the energy consumption for treating outdoor air, etc.;Robust control is prerequisite for reliable operation of the DOAS-CC system. However, control issues on the integrated system and liquid desiccant dehumidification process have been rarely concerned. The aim of this research is to develop local control methods and optimal control strategies for the DOAS-CC integrated system. It is reached through addressing the following scientific issues: (1) performance study of the membrane-based total heat exchanger; (2) control characteristics of the liquid desiccant dehumidification system; (3) system approach based optimization of DOAS-CC systems considering multiple objectives and multiple variables; (4) condensation control for chilled ceiling system.;The main works of this research are shown as follows. Firstly, a simulator for the whole DOAS-CC system is developed on TRNSYS platform to study the system performance. Mathematical models of major components are developed and validated by experimental data.;Secondly, control methods for the liquid desiccant dehumidification system in air dehumidification process and desiccant solution regeneration process are proposed and evaluated. Control characteristics of the liquid desiccant dehumidification system are also investigated.;Thirdly, control methods for the multi-zone dedicated outdoor air system are developed to decouple the indoor air temperature, humidity and ventilation controls. Performance of optimization methods on air side is evaluated by simulation tests.;Fourthly, a model-based global optimal control strategy is developed considering indoor air temperature, relative humidity and total energy consumption simultaneously. The supply air temperature and humidity of the DOAS and supply chilled water temperature are optimized by genetic algorithm.;Finally, a predictive condensation control strategy is developed for the DOAS-CC system to prevent condensation occurring at the start-up moment. Three neural network models are developed to predict the surface temperature of chilled ceiling, the indoor air dew-point temperature and the optimal prior operation time for DOAS. Performance of these models is evaluated.