基于协调的变风量空调系统递阶优化控制研究

发布时间：2018-03-01 06:04

本文关键词： 变风量空调系统节能递阶协调优化　出处：《西安建筑科技大学》2013年博士论文　论文类型：学位论文

【摘要】：中央空调是现代建筑中的能耗大户，其耗能占整个建筑能耗的50%-70%。空调系统在设计时通常采用的是最不利工况设计，一般是按照空调系统最大的负荷来进行设计的。但实际运行时，空调系统90%以上的时间都是处于部分负荷状态下的，空调系统对于负荷的处理有很大的冗余，而且在实际的空气调节中也有很大的灵活性。变风量（Variable Air Volume，VAV）空调系统是一种通过调节风量来满足室内负荷变化及舒适性要求的全空气调节系统，，由于其无凝结水害、设计系统灵活、高效节能的优点得到了广泛应用。然而，由于变风量空调系统具有非线性、大滞后、耦合性强、多变量、多扰动等特点，传统的控制方式难以适应其控制要求，使得变风量空调系统的节能性、舒适性得不到充分体现。如何通过最优化控制，使空调系统在满足环境舒适性的同时，能稳定的运行，并最大限度地减少系统能耗，就成为研究的重点。由于变风量空调系统设备较多，因此发生故障的频率也相对比较高。如果变风量空调系统中存在故障，会直接影响系统的能耗，导致系统能耗增加，并且会影响空调室内的舒适性。对于设备来说，会增加其损耗和减少其使用寿命。变风量空调系统应运行在无故障状态下，因此对于故障状态的检测就具有重要的现实意义。对与防止运行事故的发生，提高空调系统设备的有效利用时间，延长空调系统的使用寿命都具有非常良好的效果。本文通过改进的神经网络方法建立了变风量空调系统负荷模型，通过负荷的预测对变风量空调系统的能耗进行监测，并与实际的能耗检测值进行比较，利用统计学方法进行系统故障检测，能够在变风量空调系统运行过程中进行故障状态提示，确保变风量空调系统运行在无故障状态下。采用了一种基于协调的递阶优化控制，根据变风空调系统的工作原理对变风量空调大系统进行合理的分解，并通过实验对变风量空调大系统进行稳态建模，得到其稳态大系统模型。提出了其目标优化方法，以变风量空调系统舒适性和节能性为优化目标为各个控制器确立优化设定值，实现变风量空调系统的优化与节能控制。根据变风量空调系统主要部件的模型、能量平衡方程以及部件的物理限制定义了全局协调优化的目标函数和约束条件，实时优化系统各动态参数，通过寻找最优的操作条件，确定最佳工作点。并针对不同的控制回路采用不同自适应控制策略对各子系统进行稳定控制，使系统的控制参数始终维持在设定值附近。并对系统进行合理的设计、设备选型、软件选取和优化算法的实施，开发了变风量空调系统优化的计算机控制系统，对实际的操作提供了有指导意义的根据。仿真和实验研究结果表明该优化方法不仅能保证系统的舒适性而且能显著地降低系统能耗。
[Abstract]:Central air conditioning is a large household of energy consumption in modern buildings, and its energy consumption accounts for 50 to 70 percent of the energy consumption of the whole building. Air conditioning systems are usually designed under the most unfavorable conditions. It is generally designed according to the maximum load of the air conditioning system. However, when the air conditioning system is in operation, the time over 90% is in the state of partial load, and the air conditioning system has a great deal of redundancy for the handling of the load. The VAV air conditioning system is a kind of all air conditioning system which can adjust the air volume to meet the requirements of indoor load change and comfort, because it has no condensate water damage. The advantages of flexible design system, high efficiency and energy saving have been widely used. However, because VAV air conditioning system has the characteristics of nonlinear, large lag, strong coupling, multi-variable and multi-disturbance, it is difficult for the traditional control methods to adapt to its control requirements. The energy saving and comfort of VAV air conditioning system can not be fully realized. How to make the air conditioning system run stably while satisfying the environmental comfort, and reduce the energy consumption of the system to the maximum extent through the optimization control, Become the focus of research. Because VAV air conditioning system has more equipments, the frequency of failure is relatively high. If there are faults in VAV air conditioning system, the energy consumption of VAV air conditioning system will be directly affected and the energy consumption of VAV air conditioning system will increase. And it will affect the comfort of the air conditioning room. For the equipment, it will increase its loss and reduce its service life. The VAV air conditioning system should operate in a trouble-free condition. Therefore, it has important practical significance to detect the fault state. It has a very good effect on preventing the occurrence of running accidents, improving the effective utilization time of air conditioning system equipment, and prolonging the service life of air conditioning system. In this paper, the load model of VAV air conditioning system is established by improved neural network method, and the energy consumption of VAV air conditioning system is monitored by load forecasting, and compared with the actual energy consumption detection value. By using statistical method to detect the system faults, the fault state can be indicated during the operation of the VAV air conditioning system, and the VAV air conditioning system can be operated in a faultless state. A hierarchical optimal control based on coordination is adopted. According to the working principle of VAV air conditioning system, the VAV large scale air conditioning system is decomposed reasonably, and the steady state model of VAV large scale air conditioning system is established by experiments, and the model of VAV large scale air conditioning system is obtained, and its objective optimization method is presented. Taking the comfort and energy saving of VAV air conditioning system as the optimization target, the optimal setting value is established for each controller to realize the optimization and energy saving control of VAV air conditioning system. According to the model of main components of VAV air conditioning system, The energy balance equation and the physical limitation of components define the objective function and constraint conditions of global coordination optimization. The dynamic parameters of the system are optimized in real time. The optimal working point is determined, and different adaptive control strategies are adopted to stabilize the subsystems for different control loops, so that the control parameters of the system are always kept near the set value, and the system is reasonably designed and the equipment is selected. A computer control system for VAV air conditioning system optimization is developed by software selection and implementation of optimization algorithm. The simulation and experimental results show that the optimization method can not only guarantee the comfort of the system but also reduce the system energy consumption significantly.
【学位授予单位】：西安建筑科技大学
【学位级别】：博士
【学位授予年份】：2013
【分类号】：TU831

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