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中储式球磨机制粉系统先进控制和优化应用研究

The Research and Application of Advanced Control and Optimization for Ball Mill Storage Coal-pulverized System

【作者】 李宝文

【导师】 刘红波;

【作者基本信息】 山东大学 , 检测技术与自动化装置, 2009, 硕士

【摘要】 广泛应用于火电厂的钢球磨煤机中间储仓式制粉系统是典型的多变量非线性时变系统,各控制量和被控制量之间存在着相当严重的耦合,基于线性系统理论的单回路常规控制方法难以得到令人满意的控制结果,并严重影响火电机组的运行经济性和安全性。因此,研究适合于球磨机制粉系统的多变量先进控制方法,以有效地实现其自动控制和优化运行,具有十分重要的理论意义和实用价值。本文在综述了电厂球磨机中储式制粉系统先进控制方法与应用研究现状的基础上,进行了球磨机制粉系统多变量先进控制方法的应用研究。本文第一章为绪论,首先阐述了课题的背景与意义,综述了目前国内外电厂球磨机中储式制粉系统先进控制算法的研究现状和发展方向,基于目前球磨机制粉系统实际控制中存在的问题,提出了本文的主要工作内容。本文第二章针对电厂球磨机中储式制粉系统研究了多变量系统的解耦控制方法。首先分析了球磨机制粉系统的工作原理以及运行特性。球磨机制粉系统是一个多输入多输出的多变量系统。球磨机制粉系统的控制量为入口负压、出口温度和出入口压差。给煤量、再循环风量及热风量的任一改变都将影响到入口负压、出口温度和出入口压差。然后对球磨机制粉系统进行了耦合性分析,并说明多变量系统回路的配对方法,不仅要参考系统的相对增益矩阵,而且要根据实际过程的工艺和控制要求,才能选择更为合适的输入输出匹配,并以华泰电厂球磨机制粉系统数学模型为基础,对其进行了系统分析和仿真验证。由仿真结果可以看出,采用前馈补偿解耦,可以实现控制对象的近似完全解耦。本文第三章提出了一种基于多变量解耦控制和稳态优化技术相结合的控制策略。这种控制方式算法简单,易于实现。在直接控制层,为了简化控制器设计,构造两个分离矩阵,使3×3系统解耦为一个双输入双输出系统和一个单回路系统。直接控制层的任务是保证系统的稳定运行。优化控制层的任务是通过计算选择最优的设定点并传达给直接控制层,使得经济效益目标函数取得最优值。当球磨机制粉系统运行在最大出力下,制粉单耗会降到最低。因此,增加磨煤机的给煤量,意味着加快制粉系统的制粉速度,同时降低电耗。仿真结果表明此控制方案可以取得良好的控制性能。本文第四章介绍了工程设计情况。根据控制思想设计出制粉系统优化控制的总体结构,选用PLC作为制粉控制系统的下位机,并具体说明了系统的硬件设计方案,同时还说明了传感器、变送器和计算机硬件的选择和配置。接着对本系统的软件设计和实现过程进行了详细的说明。上位机采用组态王6.53实现和下位机的通讯并将制粉系统运行的全貌实时提供。可根据制粉系统实际情况计算设定制粉系统目标值,对于偏离目标值的参数提出报警等,提醒运行人员纠正偏差,提高制粉系统效率。通过仿真和离线调试,验证了本设计方案的有效性。最后对本文所做工作进行总结,并对今后工作中需要进一步探索和研究的问题进行了展望。

【Abstract】 Ball mill coal pulverized system is a multivariable coupled nonlinear time-varying system which is extensively applied in coal fired power plants. Conventional single-variable controller based on linear system theories cannot meet the control requirements. It is difficult to keep the pulverized system in safe condition and in low energy consumption in the same time. So it is of very important theoretical significance and practical value to study multivariable advanced control methods which are suitable for the ball mill coal pulverized systems, and take it into automatic control and optimal operation effectively. This paper reviews the advanced control methods and application research situation of the power plant ball mill storage pulverized coal system, and then studies the application research of the multivariable advanced control methods for ball mill coal pulverized systems.Chapter 1 is the introduction of the paper. Firstly, it describes the background and the significance of the research, and then reviews the situation and development of advanced control methods for the power plant ball mill storage pulverized coal system at present. Lastly, it puts forward the primary work based on the problems existing at practical controls of ball mill coal pulverized system.Chapter 2 studies the multivariable system decoupling control method for the ball mill storage pulverized coal system. First, this paper analyses the work theory and operation character of ball milling. The ball mill coal pulverized system is a multi-input and multi-output system. The controlled variables of ball mill are the negative pressure in the input, the temperature in the output and the difference pressure of the ball mill. The control means are to adjust the recycling air gate, the hot air gate and the coal feed quality. Then, we make the coupling analysis and give the loop matching method of multivariable system. Loop matching should not only consult relative gain array (RGA), but also have to consider the technology and control requirement of practical process to choose more appropriate input and output matching. Based on the model of the power plant, we make the system design and simulation of it. From the simulation results, we can see that the feed forward compensation decoupling control can realize the completely decoupling for controlled object.Chapter 3 proposes a control method that combined multivariable decoupling control and steady-state optimization. This method is simple and liable to apply. In direct control layer, to simplify the controller design, a 3×3 system can be decomposed into a two-input two-output (TITO) system and a single loop by constructing the two matrices A and B. The direct control layer is to keep the system running in a stable. The task of the optimization layer is to select optimal values of set-points for the lower control layer, optimizing a defined objective function of economic nature. When the ball mill coal pulverizing system is operated at about its maximal capacity of the coal stock level, the electric power consumption of pulverizing a ton of coal will be reduced to a minimum. Therefore, increasing the coal feed rate to the tube mill, i.e., increasing the feeder speed, can increase the flow rate of pulverized coal and then reduce electric energy consumption. Simulation results demonstrate the good performance of the proposed control scheme.Chapter 4 introduces the project realizes. According to the idea of designing, the overall structure of the Optimizing Control System is designed. In this system, PLC is chosen to be the lower machine, and the designing plan of hardware of this system is illustrated particularly. The configuration of sensors, converters and computer is introduced. Furthermore, the software designing and the realization of the system are illustrated precisely and meticulously. Using configuration software-King View 6.53 to realize the communication between the lower machine and the host machine, and provides the complete picture of coal pulverizing system. Operation staff may set running target value, if real-time value deviated from the target can propose alarm to remind staff to correct the deviations, which could improve operating efficiency of coal pulverizing system.At last, the author summarizes all the works which have been done in the thesis, and look forward further explorations and research questions in the next work.The research development result indicated: This system fuses the configuration software and the optimized algorithm, enhances automation level and management level of coal pulverizing system, save the energy, improve the work condition. The system will bring the obvious economic efficiency and the social efficiency.

  • 【网络出版投稿人】 山东大学
  • 【网络出版年期】2010年 04期
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