【作者】 宋新玲；

【导师】 杨建华；

【作者基本信息】 大连理工大学 ， 控制理论与控制工程， 2008， 硕士

【摘要】 随着城市建设飞速发展，节能、降耗及环保意识的增强，集中供热成为我国北方城市供热的大势所趋。它是节约燃料、改善环境及实现城市生活现代化的一项重要技术措施和政策。如何有效地控制和管理整个热力系统，提高热力系统的经济效益和社会效益，成为各供热企业急需解决的重要课题。由此导致集中供热网的运行调节和控制策略等相关问题应运而生。本文以实验室热网装置的控制为基础，旨在对集中供热网的运行调节和控制方法进行研究，主要进行了以下几方面的工作：对国内外集中供热系统的运行调节和控制技术进行了概述，并从按需供热和均匀供热的角度进行了进一步阐述。然后针对我国集中供热网的特点和存在的问题采用了适合国情的基于温度的流量控制方法。系统地讨论了集中供热系统流量调节的神经网络解耦控制策略，并针对集中供热网这种具有大滞后、大惯性、非线性、强耦合特性的系统，设计了基于非线性多变量的神经网络解耦控制器，并随后深入探讨了该控制器的特性和具体的设计思想。详细介绍了实验室热网系统硬件装置的组成、实时热网监控系统软件平台的设计开发、神经网络解耦控制器的具体实现。结果表明，该控制器能够合理的分配各热力子站一次网侧的流量，使各用户二次网供回水平均温度趋于一致，进而实现全网内热量的合理分配，提高供热网的供热质量，达到了集中供热的整体目标即稳定供热和均匀供热。更多还原

【Abstract】 Along with cities’ rapid development, people’s recognition of energy saving, consume dropping and environment protecting, the district heating supply has become the main heating mode in north China. It has been used as an important technique management and policy in saving fuel, improving environment and realizing city life’s modernization. So how to control and manage the whole heating system effectively, improve the heating system’s economy and society benefit have become the most important problem that needs to resolve for most heating supply corporations. All of these lead to the birth of correlation questions like running regulation and control policy.On the basis of Laboratory-scale heating system control, the problems of running regulation and control policy have been discussed. The application of Neural Networks technology to District Heating System to adjust the flux is also discussed. It mainly includes:The running regulation and control policy are discussed in the first part of this paper; need-based heating method and even distribution heating method are also discussed deeply. Then by analyzing the characteristics and possible problems of District Heating System in China, the flow control strategy based on temperature is presented, which adapts to the situation of our country.The method of multivariable decoupling control of Neural Networks is discussed in the second part of this paper. In accordance with the District Heating System having large delay, nonlinear and strong coupling characteristic, this paper presents a nonlinear constrained optimization controller based on multivariable decoupling controller of Neural Networks, and then the characteristic and design idea of the controller are also discussed thoroughly.It introduces the composing of Laboratory-scale heating system, the real time monitoring software platform and the implementation of multivariable decoupling controller of Neural Networks in detail. It shows that this controller can distribute the flow of the primary pipe network in every substation, make the average temperature of the supplying water and return water tend to be equal. Furthermore, it can make well-proportioned heat distribution in the whole heating network, which improves heating quality and achieves stabilization heating and even distribution heating. Meanwhile, a comfortable living environment can be created.更多还原