锅炉燃烧动态建模及多目标预测控制方法研究

发布时间：2018-03-08 08:00

本文选题：锅炉炉膛燃烧优化　切入点：炉膛一维建模　出处：《东南大学》2016年硕士论文　论文类型：学位论文

【摘要】：随着对改善大气环境质量,保护生态环境的重视,火电生产企业一方面需要提高机组运行效率,降低生产成本,另一方面需要设法解决如何降低火电机组的污染物排放的问题,以满足越来越严格的排放标准。因此,对锅炉进行燃烧优化以达到节能减排的目的具有重要的现实意义与工程应用价值。本文的主要研究内容包括：1.建立炉膛一维动态模型。通过将锅炉炉膛沿高度方向进行分层,并采用集总参数法分别描述各层内的流动、传热过程、煤粉燃烧和NOx生成过程。借助Modelica语言,在Dymola仿真平台上实现了建立锅炉炉膛一维燃烧模型,该模型能够描述煤粉量、各层风量与炉膛内各层温度、N仉浓度的动态关系,得到静稳态时炉膛一维温度分布和NOx分布。通过仿真实验研究了锅炉炉膛一维燃烧模型的动态特性,为燃烧优化策略的研究打下基础。2.采用子空间辨识方法,分别建立了100%、80%、60%负荷工况下的锅炉炉膛一维燃烧状态空间模型。该模型相比于传统的传递函数模型能够更方便地描述多变量系统,而且更有利于先进优化控制算法的设计。通过仿真实验验证子空间辨识方法对锅炉炉膛燃烧对象的建模效果。3.将多目标预测控制算法与多模型控制策略、扰动观测器相结合,建立了锅炉炉膛燃烧优化系统。锅炉炉膛燃烧优化以效率和NOx浓度为目标量,用多目标预测控制算法解决多目标优化问题,采用多模型控制策略解决大范围变工况导致的非线性问题,并引入扰动观测器抑制煤种变化带来了影响,通过仿真试验研究基于MOMPC的锅炉燃烧优化系统在变负荷、变煤质情况下的优化性能。
[Abstract]:With the importance of improving the atmospheric environment quality and protecting the ecological environment, on the one hand, the thermal power production enterprises need to improve the operating efficiency of the units and reduce the production costs, on the other hand, they need to try to solve the problem of how to reduce the emission of pollutants from thermal power units. To meet increasingly stringent emission standards. It has important practical significance and engineering application value to optimize the combustion of boiler to achieve the goal of energy saving and emission reduction. The main research contents of this paper include: 1. The one-dimensional dynamic model of furnace is established, and the boiler furnace is stratified along the direction of height. The lumped parameter method is used to describe the flow, heat transfer process, pulverized coal combustion and NOx generation process in each layer respectively. With the help of Modelica language, a one-dimensional combustion model of boiler furnace is realized on the Dymola simulation platform, which can describe the pulverized coal quantity. The dynamic relationship between the air flow in each layer and the temperature concentration in each layer of the furnace is obtained. The one-dimensional temperature distribution and the NOx distribution of the furnace under static and steady state are obtained. The dynamic characteristics of the one-dimensional combustion model of the boiler furnace are studied by simulation experiments. Laying the foundation for the research of combustion optimization strategy. 2. Using subspace identification method, The one-dimensional combustion state space model of boiler furnace under 60% load condition is established respectively. Compared with the traditional transfer function model, the model can describe the multivariable system more conveniently. Moreover, it is more beneficial to the design of advanced optimal control algorithm. The modeling effect of subspace identification method on boiler furnace combustion object is verified by simulation experiments. 3. The multi-objective predictive control algorithm is combined with multi-model control strategy and disturbance observer. The combustion optimization system of boiler furnace is established. The multi-objective optimization problem is solved by multi-objective predictive control algorithm, which takes efficiency and NOx concentration as the target quantity. The multi-model control strategy is used to solve the nonlinear problem caused by a wide range of off-condition conditions, and the disturbance observer is introduced to suppress the change of coal. The simulation experiment is conducted to study the variable load of the boiler combustion optimization system based on MOMPC. Optimized performance under the condition of changing coal quality.
【学位授予单位】：东南大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TM621.2

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