基于模型预测控制的换热站质调节研究

发布时间：2018-01-11 18:32

本文关键词：基于模型预测控制的换热站质调节研究　出处：《大连海事大学》2017年硕士论文　论文类型：学位论文

【摘要】：当前热水供热系统通常采用整体质调节的方式进行运行调节。换热站的局部运行调节不直接跟踪室温而是以水温作为被控量,水温给定通常由经验设定。热源作起主导作用的调节方式没能充分发挥换热站的水温调节能力。水温与室温间存在一个散热升温环节,在多变的天气情况和不同的建筑蓄热状况共同作用下,根据经验确定的水温给定难以保证室温响应的准确,故时常引起用户室温偏高或偏低。本文针对上述问题,将天气因素考虑在内,建立特定换热站供热区域内水温到室温的热动态模型。以此模型作为预测模型,应用模型预测控制,参照分时供热的室温参考轨迹制定换热站二次网供水温度,换热站依此进行质调节。本文主要研究内容如下:1.建模部分中,分析热动态响应的特点和用线性时不变的离散状态空间模型描述热动态的合理性;依据相关研究成果确定模型的输入、输出和采样周期;应用子空间辨识这种黑箱辨识方法,辨识得到模型;对模型的可用性进行验证,选取响应合理的模型作为预测模型。2.设计模型预测控制器,进行参数整定。考虑到室温容易受到扰动,提出可采用只使用二次网回水温度作为测量量的观测器进行状态观测,这样能够以较小的精度损失获取更好的抗干扰能力。分时间段进行闭环仿真,将室温仿真结果与历史测量数据进行对比;进一步进行改变约束条件、不使用扰动量预测值和模型失配情形下的仿真,并比较控制效果。3.面向工程应用,讨论输入预报值的获取;给出两层控制结构中上层计算给定的两种配置方式;分析可能出现的电能浪费和换热站大幅调节对一次网可能产生的不利影响,并分别制定了相应的对策。由仿真结果得出结论:按照模型预测控制制定的二次网供水温度进行换热站运行调节,能使室温更好的跟踪参考轨迹,保证用户室温更平稳运行,并实现能效的提高。室温超调和不达标的情况得到了明显改善;即使在改变约束条件和模型失配的情形下,室温也得到了较好的改善。
[Abstract]:At present, the hot water heating system usually adopts the way of integral quality regulation. The local operation regulation of the heat exchange station does not directly track the room temperature, but takes the water temperature as the controlled quantity. The water temperature is usually set by experience. The heat source plays a leading role in regulating the water temperature. There is a link between water temperature and room temperature. Under the combined action of variable weather conditions and different building heat storage conditions, it is difficult to ensure the accuracy of room temperature response when the water temperature determined by experience is given. This paper takes the weather factors into account and establishes a thermal dynamic model of water temperature to room temperature in the heating area of a specific heat transfer station. The model is used as a prediction model. Using model predictive control, referring to the room temperature reference track of time-sharing heating, the secondary network water supply temperature of heat exchange station is determined, and the heat exchange station carries on the quality adjustment according to this. The main contents of this paper are as follows: 1. In the modeling part. The characteristics of thermal dynamic response and the rationality of describing thermal dynamic by linear time-invariant discrete state space model are analyzed. The input, output and sampling periods of the model are determined according to the related research results. The black box identification method is used to identify the model. The availability of the model is verified, and the model with reasonable response is selected as the prediction model. 2. The model predictive controller is designed to adjust the parameters. A state observation observer using only the backwater temperature of the secondary network is proposed, which can obtain better anti-jamming ability with less precision loss. The closed-loop simulation is carried out in different time periods. The room temperature simulation results are compared with the historical measurement data. Further change the constraint condition, do not use the disturbance prediction value and model mismatch simulation, and compare the control effect .3.Orient to the engineering application, discuss the input prediction value acquisition; Two configuration methods for upper layer calculation of two-layer control structure are given. The possible energy waste and the adverse effects of heat transfer station adjustment on primary network are analyzed. According to the simulation results, it is concluded that the heat transfer station can be operated and adjusted according to the water supply temperature of the secondary network based on the model predictive control, which can make the reference track track better at room temperature. Ensure that the user runs more smoothly at room temperature, and realize the improvement of energy efficiency. Even when the constraint conditions and the model mismatch are changed, the room temperature is improved.
【学位授予单位】：大连海事大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TU995;TP273

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