溶液除湿空调动态传热传质建模与多目标优化控制研究

Liquid Desiccant Air Conditioning (LDAC) is a novel air conditioning with benefits of energy saving, independent air temperature and humidity control, better air quality, and with wide-developing prospects in building energy conservation. However, the research on dynamic analysis of heat and mass transfer between air and desiccant solutions, energy-efficiency-oriented optimal control strategies moves so slowly, and its energy saving performance is so far away from satisfying that limiting its development in building energy conservation. To develop the optimal control strategy for energy savings in LDAC, the project plans to explore the mechanism of dynamic heat and mass transfer, develop the control-oriented hybrid model, and to propose a LDAC real-time and accurate energy consumption prediction method based on Genetic Algorithm and Support Vector Machine. Then Multiobjective Optimal Control that considers system energy consumption, dynamic performance, trajectory tracking performance and control output increments as optimization objectives is investigated. The proposed Multiobjective Optimal Control Strategy is then designed and implemented on a small scale LDAC testing platform. Experiment studies are carried out to discuss the feasibility and energy saving performance of the proposed optimal control strategy. The investigation of the project will help to reveal the mechanism of dynamic heat and mass transfer in LDAC systems, provide theoretical basis and solutions to develop optimal control strategy for further energy savings in LDAC and are with great significance for theory and application in further energy efficiency improvement of LDAC and its developments in building conservation.

溶液除湿空调（LDAC）是一种具有节能、温湿度独立调控和净化空气优点的新型空调，在建筑节能领域具有广阔应用前景。然而系统动态传热传质机理分析和面向系统能效的优化控制研究进展十分缓慢，导致LDAC能源利用效率不尽如人意，严重制约了其在建筑节能领域的快速发展。本项目拟针对LDAC优化控制问题与节能降耗需求，探索空气与溶液间动态传热传质机理并构建面向控制的混合模型；同时研究基于遗传算法和支持向量机的LDAC能耗实时准确预测方法；进而基于预测控制提出以能耗、动态响应、参考轨迹跟踪性能和控制律变化程度为优化目标的多目标优化控制理论与方法；通过多目标优化控制器设计和试验研究来验证项目研究理论的可行性与节能效果。本项目的研究将有助于揭示LDAC动态传热传质机理，为系统优化控制提供理论基础和有效解决方案，对充分挖掘LDAC节能潜力、提高能源利用效率、促进其在建筑节能领域发展具有重要的理论意义和应用价值。

溶液除湿空调（LDAC）系统的优化控制对于推动其在建筑空调节能领域的发展具有重要意义。本项目针对LDAC动态传热传质建模与多目标优化控制问题。首先，基于动量守恒、能量质量守恒和传热传质理论研究LDAC系统的动态传热传质机理，结合神经网络模型和模糊模型的建模优势，提出自适应神经模糊系统（Adaptive Neuro-Fuzzy Inference System, ANFIS）建模方法，通过ANFIS建立以溶液温度和流量为输入变量，溶液浓度、换热器进口溶液温度等为系统状态变量，系统出口空气温度和湿度为输出变量的面向控制LDAC动态传热传质混合模型；其次，基于TRNSYS软件建立了太阳能驱动LDAC系统的动态仿真平台，同时基于仿真平台数据建立LDAC系统能耗的预测模型，实现外界温度、湿度，LDAC系统溶液温度、流量等参数变化时系统的动态输出特性及能耗变化特性分析，为研究系统优化控制策略奠定基础；最后，针对LDAC系统提出了经济模型预测控制（EMPC）优化策略，构造包含系统控制和能耗的目标函数，建立有限时域动态优化问题，并利用遗传算法求解动态优化问题，分析了不同工况下本项目研究优化策略的有效性。本项目的研究提高了LDAC系统的能源利用率，对于促进其在空调领域的应用具有重要意义。在该项目的资助下，发表学术论文11篇，其中SCI论文4篇，EI会议论文7篇，其中1篇荣获第十三届IEEE Conference on Industrial Electronics and Application最佳论文奖，1篇荣获山东大学2020年研究生优秀学术成果奖；在本项目的研究成果基础上，申请获批国家基金面上项目及山东省重大科技创新工程项目。联合培养博士1人，现就任青岛大学副教授; 培养硕士生9人，其中毕业4人，1位毕业生赴上海交通大学继续攻读博士学位，其余3人在华为、亚控等高新技术企业工作。

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