节点文献

集中供热系统运行方式及管网泄漏检测研究

Research on Operation Modes and Pipeline Leak Detection in Central Heating System

【作者】 杨先亮

【导师】 王松岭;

【作者基本信息】 华北电力大学 , 热能工程, 2015, 博士

【摘要】 随着我国经济的持续发展,能源和环境问题日益突出。在我国建筑能耗中,采暖能耗所占的比例最大,而且单位住宅建筑采暖能耗是相同气候条件下发达国家的3倍左右,因此对集中供热系统的节能性研究势在必行。集中供热系统由热源、供热管网和热用户三部分组成,本文从集中供热系统的组成着手,分别对系统热源调节方式、供热管网泄漏定位及热用户的室温控制、洗浴废水余热回收进行研究。论文的研究内容包括以下几个方面。针对热源节能调节,建立了分阶段质量-流量动态调节模型,并运用Matlab软件对该动态模型进行实例仿真计算,得到了供、回水温度及流量随室外温度变化的变化规律。通过在分阶段改变流量的质调节、分阶段质量-流量稳态调节及动态调节三种调节方式下对系统的二次网年耗电量及热源耗煤量对比分析,得到了在热源处采用分阶段质量-流量动态调节方式二次网耗电量、热源耗煤量、污染物排放量均最少,其节能性更明显。针对热用户节能,建立了分户计量系统二次网的供热调节模型及升温模型,通过实例仿真计算,得到了供回水温度、流量及供热负荷随室外温度变化的变化规律,为该系统的节能运行提供了理论依据。设计了带换热装置的节能地漏,并对该装置进行实验分析及数值模拟,表明该地漏能有效回收热用户沐浴废水的热量。针对供热管网泄漏定位,自行设计并搭建了供热管网泄漏检测综合实验系统;提出并利用多种群混合自适应遗传算法、混合自适应遗传算法对热力管网阻抗进行辨识,并通过了实验验证。实验结果表明,无论管网在稳定工况还是泄漏工况,两种算法均能提高计算精度,且多种群混合自适应遗传算法计算精度较高。建立了图论与混合自适应遗传算法相结合的热力管网阻力数矩阵,对管网泄漏后各换热站水力工况参数的变化特性进行了模拟,得到了泄漏时供水管段换热站入口节点压力、回水管段换热站进出口节点压力差及流量随泄漏位置的变化规律,进而确定出泄漏管段;根据压力梯度定位原理,建立了泄漏点定位模型,在泄漏管段上计算了泄漏点的相对位置,并进行了实验验证。实验结果表明,运用热力管网阻力数矩阵模拟管网泄漏时得出的供水管段换热站入口节点压力、回水管段换热站进出口节点压力差及流量随泄漏位置的变化规律是正确的;泄漏点定位计算误差率最大为5.54%,最小误差率为0.25%,能够满足工程需要。

【Abstract】 As China’s sustained economic development, energy and environmental problems become increasingly prominent. In the building energy consumption in our country, the energy consumption for heating the largest proportion, and the unit of residential building heating energy consumption is about 3 times the same climatic conditions in developed countries, so the research on energy-saving of central heating system should be imperative. The central heating system consists of heat source, heat supply network and hot user of three part, this article proceed from the composition of central heating system, studied the syetem of heat source regulation mode, heating pipelines leak positioning and heat users’room temperature control, bathing waste water waste heat recovery separately.Research paper includes the following aspects:In view of the heat source energy saving control, established phased quality flow dynamic adjustment model, using Matlab software for simulation calculation of the dynamic model, and got the change rule of supply, return water temperature and flow with the outdoor temperature changes. By changing the flow of quality regulation in stages, staged mass-flow homeostatic regulation and dynamic adjustment three kinds of control method and analysising comparatively the secondary network system power consumption and heat coal consumption, Obtained by stages of mass-flow dynamics regulation mode in the heat source, the secondary network system power consumption, heat coal consumption, pollutant emissions are the least,and the energy-saving is more obvious.In order to analyze the method of leakage location, the comprehensive experiment heating pipeline leakage detection system is built. The methods of multi-population hybrid adaptive genetic algorithm and mixture adaptive genetic algorithm are used to do the identification of resistance in heating pipeline. The experimental results show that the two methods of genetic algorithm could improve the accuracy of identification. And the multi-population hybrid adaptive genetic algorithm has the higher accuracy.The matrix of resistance which is used in heating pipe line is built on the base of graph theory and hybrid adaptive genetic algorithm. The variations of working conditions in different running conditions arc simulated. The change rule of the pressure of heat exchange station entrance in the leakage condition of water supply pipe is calculated. The change rule of pressure differential of heat exchange station entrance and outlet, flow is calculated too. The leakage section could be located with this change rule. Then, the leakage location model is built on the base of pressure gradient. The leakage point could be found with this model. At the end, the experiment is used to show the accuracy of those theories. The experiment result expresses that the change rule is right. The maximal error of the location of leakage point is 5.54%. The minimum error of the location of leakage point is 0.25%. This theory meets require of heating engineering.

  • 【分类号】TU995
  • 【被引频次】9
  • 【下载频次】675
节点文献中: 

本文链接的文献网络图示:

本文的引文网络