Modeling and control of dehumidifier in distributed operating liquid desiccant dehumidification system
Date of Issue2017
Interdisciplinary Graduate School
Liquid Desiccant Dehumidification System (LDDS) achieves low humidity level with relatively low energy consumption, which is an outstanding alternative to conventional air-conditioning system in removing the moisture in the air. In industrial or commercial buildings, dehumidifiers of LDDS are usually located at different floors in a distributed manner, while the heat source utilized for regeneration such as the waste heat or solar energy are in the plant room or on the rooftop in a centralized form. Conventional LDDSs regulate the solution concentration in the dehumidifier by continuously exchanging the desiccant solution between dehumidifier and regenerator, which limits LDDS to a one dehumidifier vs. one regenerator arrangement. To take full advantage of the building recourses, a scheme of multiple dehumidifiers working with one regenerator is more efficient. Meanwhile, new technical issues have been raised together with this mechanism, such as detecting and maintaining solution concentration and the solution transfer among the components of a system with multiple terminals. Therefore, this thesis tries to provide some deep discussions on the questions generated from the distributed operating manner to further popularize LDDS in building application. The major contributions are as follows: A buffer integrated dehumidifier has been proposed to realize the distributed operation, and new mathematical model has been developed and validated to describe the dynamic profiles of the dehumidification and concentration variation process during the system operating, including the moisture absorption, strong solution charging, solution mixing, circulating and excavating. A concentration regulation strategy has been developed to control the working solution concentration in the dehumidifier. Model-based soft-sensors are designed to detect the working solution concentrations of dehumidifier and regenerator to provide the concentration information of the two towers for the regulation strategy. Experimental studies on an actual system have been carried out to further verify the efficiency of this concentration regulation strategy with the assistance of the soft-sensors. By considering the relations between working solution concentration and energy consumptions, Genetic Algorithm (GA) is employed to obtain the optimal combination of weak and strong desiccant concentrations, solution and chilled water mass flow rates in dehumidification side for energy-saving purpose. Component and overall energy consumptions have been discussed and compared to analyze the energy performance at different working conditions to justify the distinctions of the GA selected input pairs among those applicable input combinations. The working solution concentrations in dehumidifier and regenerator are measured and regulated to the optimal combination generated from the GA optimizer, and the fuzzy-PID controller tunes the outlet air humidity by regulating the inlet solution temperature. The indices IAE, ITAE and ISE are utilized to evaluate the performances of these combined modules. With some simplifications, these strategies are applied on a test rig following the distributed operating strategy to validate the feasibility of the proposed method.
DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering