先进控制策略在单元机组协调控制系统中的应用研究
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摘要
单元机组系统简单,具有蒸汽管道比较短,阀门和管道附件比较少,发电机母线短,从而使得单元机组投资少、操作简单、系统事故发生机会减少,同时也使得单元机组可以较好地进行滑参数运行和滑参数启、停。另外,单元机组也便于锅炉、汽轮机、发电机的集中控制和运行,因此,单元机组在我国火电机组中占有较大的比重。随着电力需求的不断增长,科学技术的不断进步和对机组经济性能要求的不断提高,大容量、高参数、高自动化技术的大单元机组已经成为我国电力工业发展的主要特点。目前,单元机组协调控制系统中其控制策略均采用常规PID加前馈补偿方式。因火电机组控制对象的复杂性,其设备和工作原理涉及多个领域,多个变量,动态特性具有非线性、大滞后和时变等特点,这种基于单回路固定模型的传统控制策略限制了控制品质的提高,因此开发出适合火电过程控制的先进控制策略具有重要意义。
在这种传统的方式下,锅炉和汽轮机已结合成一个联合的调节对象,以其内部的协调配合来最大限度地满足电网的负荷要求。协调机组的内部关系,也就成为单元机组主控系统所要解决的问题.单元机组主控系统是协调控制系统的核心,是整个单元机组自动调节系统的指令系统,它把外部对单元机组的负荷要求信号进行处理,使它转化为适合于机、炉运行状态和变动负荷能力,并发出使机、炉配合动作的指令协调控制系统是单元制发电机组的控制中枢,是现代电站自动化系统中最为核心的组成单元。本文应用线性多变量控制及非线性控制的相关原理和方法研究了单元机组协调控制系统的设计、整定、工程实现等问题,致力于推动先进控制策略的工程应用,提高协调控制系统对过程非线性的适应能力。
本文深入研究了非线性、多变量热工对象的先进控制策略问题,主要内容归纳为如下：
针对非线性多变量对象,本文首先应用常规的模糊控制方法和模糊自适应非线性控制策略应用于单元机组负荷控制中,使单元机组非线性引发的解耦模型无法实现和线性控制器品质差的问题,得到有效解决。文中就常规模糊控制应用于单机组控制中,设计了规则少的模糊非线性在线新型控制器,为模糊控制理论在负荷控制中的工程实际作了新的尝试。在研究中发现,对于高阶系统,参数估计的高阶导数将会出现在控制率中,所以,自适应反馈线性化不能被用到通过反馈线性化的所有系统。为了解决单元机组协调控制中的此类问题,在常规的Backstepping方法基础上,提出了一种新的方法,自适应模糊控制的Backstepping设计方法,并将应用到机组协调控制中,收到了良好的效果。
单元机组协调控制系统中的锅炉主蒸汽温度是电厂生产运行中的一个非常重要的监测和控制参数,过高或过低都会影响到机组的安全性和经济性,一般要求主蒸汽温度基本上维持在额定值(即给定值)附近。主蒸汽温度的控制多年来一直是电厂过程控制中的一个难点,这主要是因为：首先,主蒸汽温度被控对象总是存在一定的迟延,而且机组容量越大迟延就越严重,常常使得反馈控制作用来不及进行调节；其次,主蒸汽温度被控对象的动态特性随着工况的变化会发生变化,即其数学模型在不同的工况下是不同的,这会导致参数固定不变的控制器在变工况情况下的实际控制效果恶化；另外,主蒸汽温度被控对象的动态特性是非线性的,也增加了控制的难度。针对电厂过程控制中主蒸汽温度的大迟延性、非线性和时变性,本文在充分分析主蒸汽温度被控对象动态特性和现场实际情况的基础上,对主蒸汽温度被控对象采用了工程上可实现的模糊自适应控制方案。
提出了将自适应逆控制作为一种新的方法,应用于复杂、未知的和不确定的单元机组协调控制中,通过逆系统方法和模糊自适应逆控制两种方法对单元机组典型负荷下的控制进行系统设计和仿真试验。证明方法的可行性。
针对多输入多输出非线性的单元机组协调控制系统,提出了一种非常易于工程实现的控制方法,即采用静态神经网络和若干积分器组成的动态神经网络逆系统方法,对被控对象进行“线性化”并解耦,然后对线性化解耦后的各线性子系统设计了闭环控制器,从而获得优良的静、动态特性与抗干扰能力。本文中对该方法的工程实现进行了详细阐述。
最后对全文作出总结,并提出了下一步研究的方向。
Unit plant has some advantages, such as simple system, short steam pipe, few valve and pipe accessory, and short generator bus, which makes less investment, simpler operation, less accident and unit sliding-parameter running and startup or shutdown better. In addition, the unit also facilitates the centralized operation for the boiler, turbine and generator. Therefore, the unit account for high proportion in power plant in china. With the continuous demand of electricity, the progress of science and technology and high requirement of unit economical performance, main characteristics of power industry is focused on the large capacity and high parameters good automation technology for the unit plant. In present, the control strategies of the unit coordinated control system still depend on PID and feed-forward compensation theory. Because of complex control objects, unit plant involves several domains and multivariable in its equipment and principle, and has some features of time-delay and time-varying nonlinear dynamic property. Furthermore, traditional control strategy based on single loop model limits the quality of the control system. So it is significant to explore advanced control strategy to enhance power process.
Boiler and turbine are combined into a control object in traditional method, which is adjusted by internal coordination to satisfy the requirement of power network load to the greatest extent. Then, coordinating the internal relationship becomes the major problem of main control system of unit plant. In addition, the main control system is the core of coordinated control system, and is the instruction system of the whole unit plant in automatic regulation. Signal from external requirements for the load of the unit plant is processed and transformed by main control system for better operation states of plant and boiler. The main control system is the key part of the unit generator with instructions which is used to coordinate the boiler and turbine better, is an indispensable core of modern automatic power plant. In this paper, the design and realization of the unit coordinated control system are studied based on the linear multiple-variable control and nonlinear control theory and methods in order to enhance the application of advanced control strategy and improve the adaptability of coordinated control system for the nonlinear process.
In this paper, we concern with the nonlinear and multivariable thermal object with advanced control strategy, the main research is as follows:
For the nonlinear multivariable problem, fuzzy control method and fuzzy adaptive nonlinear control strategy are applied in the load control of unit plant, which solved decoupling model realization and quality of linear controller due to the nonlinear characteristic in unit plant. The nonlinear fuzzy controller of unit plant with fewer rules is designed in a new way for the engineering. For the high order system, the higher derivative of parameter estimation appeared in the control rate. So the adaptive feedback linearization can not be applied in all feedback linearization systems. In order to solve this problem in unit plant, a new method, fuzzy adaptive control based on back-stepping, is proposed, and it has got a good result in coordinated control of unit plant.
Main steam temperature of boiler in the unit coordinated control system is a important monitoring and control parameter, and much higher or lower temperature will both have negative influence in safety and economy. Generally, it is required to maintain the main steam temperature at the constant value, which is a difficult problem in the process control of power plant. The reasons are as follows:firstly, there exists time-delaying in the object of main steam temperature. The larger the capacity is, the worse the time-delaying is. So it can not be adjusted in time with the feedback control method; secondly, the dynamic characteristic of main steam temperature is changed with the variant working conditions. It is that the mathematic model is changed with the variant working conditions, which cause bad adjustment with the fixed controller. Furthermore, the dynamic and nonlinear object of main steam temperature can also increase the difficulty of adjustment. For the large time-delaying, nonlinear and time-varying characteristic in process control, fuzzy adaptive method is applied in main steam temperature based on the analysis of practical situation.
The adaptive inverse control method is proposed in the application on the complex, unknown and uncertain coordinated control of unit plant. Two methods, inverse system method and fuzzy adaptive inverse control method, are designed for the typical load of unit plant. Finally the simulative results prove the feasibility of these methods.
For the MIMO nonlinear unit coordinated control system, a new method is presented based on static neural network, dynamic neural network with some integrators and inverse system method, and it is simple and easy to be realized. After linearization and decoupling for the objects, a closed-loop controller of subsystem is designed with better static, dynamic and anti-interference ability. Of course, the realization process of the method is deeply expatiated.
In the end, summary and future research prospect are given.
在这种传统的方式下,锅炉和汽轮机已结合成一个联合的调节对象,以其内部的协调配合来最大限度地满足电网的负荷要求。协调机组的内部关系,也就成为单元机组主控系统所要解决的问题.单元机组主控系统是协调控制系统的核心,是整个单元机组自动调节系统的指令系统,它把外部对单元机组的负荷要求信号进行处理,使它转化为适合于机、炉运行状态和变动负荷能力,并发出使机、炉配合动作的指令协调控制系统是单元制发电机组的控制中枢,是现代电站自动化系统中最为核心的组成单元。本文应用线性多变量控制及非线性控制的相关原理和方法研究了单元机组协调控制系统的设计、整定、工程实现等问题,致力于推动先进控制策略的工程应用,提高协调控制系统对过程非线性的适应能力。
本文深入研究了非线性、多变量热工对象的先进控制策略问题,主要内容归纳为如下：
针对非线性多变量对象,本文首先应用常规的模糊控制方法和模糊自适应非线性控制策略应用于单元机组负荷控制中,使单元机组非线性引发的解耦模型无法实现和线性控制器品质差的问题,得到有效解决。文中就常规模糊控制应用于单机组控制中,设计了规则少的模糊非线性在线新型控制器,为模糊控制理论在负荷控制中的工程实际作了新的尝试。在研究中发现,对于高阶系统,参数估计的高阶导数将会出现在控制率中,所以,自适应反馈线性化不能被用到通过反馈线性化的所有系统。为了解决单元机组协调控制中的此类问题,在常规的Backstepping方法基础上,提出了一种新的方法,自适应模糊控制的Backstepping设计方法,并将应用到机组协调控制中,收到了良好的效果。
单元机组协调控制系统中的锅炉主蒸汽温度是电厂生产运行中的一个非常重要的监测和控制参数,过高或过低都会影响到机组的安全性和经济性,一般要求主蒸汽温度基本上维持在额定值(即给定值)附近。主蒸汽温度的控制多年来一直是电厂过程控制中的一个难点,这主要是因为：首先,主蒸汽温度被控对象总是存在一定的迟延,而且机组容量越大迟延就越严重,常常使得反馈控制作用来不及进行调节；其次,主蒸汽温度被控对象的动态特性随着工况的变化会发生变化,即其数学模型在不同的工况下是不同的,这会导致参数固定不变的控制器在变工况情况下的实际控制效果恶化；另外,主蒸汽温度被控对象的动态特性是非线性的,也增加了控制的难度。针对电厂过程控制中主蒸汽温度的大迟延性、非线性和时变性,本文在充分分析主蒸汽温度被控对象动态特性和现场实际情况的基础上,对主蒸汽温度被控对象采用了工程上可实现的模糊自适应控制方案。
提出了将自适应逆控制作为一种新的方法,应用于复杂、未知的和不确定的单元机组协调控制中,通过逆系统方法和模糊自适应逆控制两种方法对单元机组典型负荷下的控制进行系统设计和仿真试验。证明方法的可行性。
针对多输入多输出非线性的单元机组协调控制系统,提出了一种非常易于工程实现的控制方法,即采用静态神经网络和若干积分器组成的动态神经网络逆系统方法,对被控对象进行“线性化”并解耦,然后对线性化解耦后的各线性子系统设计了闭环控制器,从而获得优良的静、动态特性与抗干扰能力。本文中对该方法的工程实现进行了详细阐述。
最后对全文作出总结,并提出了下一步研究的方向。
Unit plant has some advantages, such as simple system, short steam pipe, few valve and pipe accessory, and short generator bus, which makes less investment, simpler operation, less accident and unit sliding-parameter running and startup or shutdown better. In addition, the unit also facilitates the centralized operation for the boiler, turbine and generator. Therefore, the unit account for high proportion in power plant in china. With the continuous demand of electricity, the progress of science and technology and high requirement of unit economical performance, main characteristics of power industry is focused on the large capacity and high parameters good automation technology for the unit plant. In present, the control strategies of the unit coordinated control system still depend on PID and feed-forward compensation theory. Because of complex control objects, unit plant involves several domains and multivariable in its equipment and principle, and has some features of time-delay and time-varying nonlinear dynamic property. Furthermore, traditional control strategy based on single loop model limits the quality of the control system. So it is significant to explore advanced control strategy to enhance power process.
Boiler and turbine are combined into a control object in traditional method, which is adjusted by internal coordination to satisfy the requirement of power network load to the greatest extent. Then, coordinating the internal relationship becomes the major problem of main control system of unit plant. In addition, the main control system is the core of coordinated control system, and is the instruction system of the whole unit plant in automatic regulation. Signal from external requirements for the load of the unit plant is processed and transformed by main control system for better operation states of plant and boiler. The main control system is the key part of the unit generator with instructions which is used to coordinate the boiler and turbine better, is an indispensable core of modern automatic power plant. In this paper, the design and realization of the unit coordinated control system are studied based on the linear multiple-variable control and nonlinear control theory and methods in order to enhance the application of advanced control strategy and improve the adaptability of coordinated control system for the nonlinear process.
In this paper, we concern with the nonlinear and multivariable thermal object with advanced control strategy, the main research is as follows:
For the nonlinear multivariable problem, fuzzy control method and fuzzy adaptive nonlinear control strategy are applied in the load control of unit plant, which solved decoupling model realization and quality of linear controller due to the nonlinear characteristic in unit plant. The nonlinear fuzzy controller of unit plant with fewer rules is designed in a new way for the engineering. For the high order system, the higher derivative of parameter estimation appeared in the control rate. So the adaptive feedback linearization can not be applied in all feedback linearization systems. In order to solve this problem in unit plant, a new method, fuzzy adaptive control based on back-stepping, is proposed, and it has got a good result in coordinated control of unit plant.
Main steam temperature of boiler in the unit coordinated control system is a important monitoring and control parameter, and much higher or lower temperature will both have negative influence in safety and economy. Generally, it is required to maintain the main steam temperature at the constant value, which is a difficult problem in the process control of power plant. The reasons are as follows:firstly, there exists time-delaying in the object of main steam temperature. The larger the capacity is, the worse the time-delaying is. So it can not be adjusted in time with the feedback control method; secondly, the dynamic characteristic of main steam temperature is changed with the variant working conditions. It is that the mathematic model is changed with the variant working conditions, which cause bad adjustment with the fixed controller. Furthermore, the dynamic and nonlinear object of main steam temperature can also increase the difficulty of adjustment. For the large time-delaying, nonlinear and time-varying characteristic in process control, fuzzy adaptive method is applied in main steam temperature based on the analysis of practical situation.
The adaptive inverse control method is proposed in the application on the complex, unknown and uncertain coordinated control of unit plant. Two methods, inverse system method and fuzzy adaptive inverse control method, are designed for the typical load of unit plant. Finally the simulative results prove the feasibility of these methods.
For the MIMO nonlinear unit coordinated control system, a new method is presented based on static neural network, dynamic neural network with some integrators and inverse system method, and it is simple and easy to be realized. After linearization and decoupling for the objects, a closed-loop controller of subsystem is designed with better static, dynamic and anti-interference ability. Of course, the realization process of the method is deeply expatiated.
In the end, summary and future research prospect are given.
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