发电过程控制系统的综合性能评价策略研究
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摘要
电力关乎国计民生,是社会经济发展的动力之源。无论是传统的发电方式还是新型能源发电方式,在一次能源向电能的转换过程中都要经历复杂的物理、化学过程,而这些过程往往包含着众多的设备和部件。
在现代化的电厂中,控制系统遍布于整个生产流程,指挥着各设备和部件按照既定技术指标和运行规程自动、协同地运行。随着能源危机和环境问题的日益突显,控制系统又进一步担负起除安全稳定运行之外的更多职能。在这种情况下,控制系统的性能将直接影响发电机组的运行品质及其输出电能的质量。
本文针对发电过程控制系统的性能评价问题展开研究,主要工作及取得创新性成果体现在如下三个方面：
针对影响控制系统性能及评价结果的重要影响因素——非线性度,提出了基于最小方差下界比的非线性度量指标。该度量指标基于Hammerstein结构定义,同时适用于Winner结构和Winner-Hammerstein结构。针对该指标,给出了基于闭环操作数的指标估计算法,并应用统计推断原理给出了非线性度强弱的判定区间。通过仿真对比,验证了该非线性度量指标及其估计算法的有效性,并以磨煤机出口温度控制系统的非线性度量为例进行了实例仿真研究。
提出了评价线性高斯系统控制性能的最小信息熵基准,并将该基准推广到非线性非高斯系统。基于该基准定义了非线性非高斯系统的性能评价指标,进而给出非线性非高斯系统的性能评价方法。仿真对比验证了所提出性能指标和评价方法的有效性,并以磨煤机出口温度控制系统为例,研究了发电过程单回路控制系统的性能评价问题。
提出了一种基于线性解耦滤波的多变量控制系统性能评价方法。该方法可通过解耦滤波将多输入多输出系统转化多个单输入单输出系统进行评价,并给出各个回路对于系统整体性能的影响程度。在该评价方法的基础上,应用自举重采样方法实现了回路级的性能诊断。以火电机组汽轮机负荷转速多变量控制系统为例,对该方法的有效性进行了仿真验证。
Electric power relates the national economy and people's livelihood and is the source of social economy development. No matter traditional or new ways of generating energy power generation, the process of energy conversion to electrical energy goes through complex physical and chemical processes, and these processes often contain a large number of equipment and components.
In modern power plants, the control system is throughout the entire production process, and commands various equipment and components running automatically, and cooperatively in accordance with established specifications and operating procedures. With the increasing energy crisis and environmental problems, the control system further shoulders more functions in addition to the safe and stable operation. In this case, the performance of the control system will directly affect not only the running quality of the units but also the quality of output power.
This paper studies the control system performance evaluation in power generation process., the main contributions of this dissertation are given as following:
Nonlinearity is an important factor that affecting the control performance and the evaluation results. A nonlinearity measure based on minimum variance lower bound ratio is presented in this paper to qualify the nonlinear degree of closed loop systems. This measure is deduced from Hammerstein structure, but it also can be applied to Wiener structure and Wiener-Hammerstein structure. Besides, this measure can be estimated from the routine operating data. The threshold to judging whether nonlinearity is strong or weak is given by the principle of statistic interval. The effectiveness and consistency of this measure are illustrated by four simulations. The nonlinearity measure of coal mill outlet temperature control is given as an application example.
A minimum information entropy benchmark is proposed for assessing linear Guassian system and is extented to nonlinear non-Gaussian system. Then, a minimum information entropy based performance index is defined and the control performance assessment procedures are developed. Simulation tests and an industrial case study of coal mill outlet temperature control system are utilized to verify the effectiveness of the proposed procedures.
A new MIMO control system method based on output filtering is presented. This method can transform MIMO control performance assessment into multiple SISO control performance assessment by output filtering. The importance of every loop is obtained. With this CPA framework, a performance diagnosis method is presented with respect to the bootstrap resampling. The turbine load/speed control system is selected to test the effectiveness of the proposed procedures
在现代化的电厂中,控制系统遍布于整个生产流程,指挥着各设备和部件按照既定技术指标和运行规程自动、协同地运行。随着能源危机和环境问题的日益突显,控制系统又进一步担负起除安全稳定运行之外的更多职能。在这种情况下,控制系统的性能将直接影响发电机组的运行品质及其输出电能的质量。
本文针对发电过程控制系统的性能评价问题展开研究,主要工作及取得创新性成果体现在如下三个方面：
针对影响控制系统性能及评价结果的重要影响因素——非线性度,提出了基于最小方差下界比的非线性度量指标。该度量指标基于Hammerstein结构定义,同时适用于Winner结构和Winner-Hammerstein结构。针对该指标,给出了基于闭环操作数的指标估计算法,并应用统计推断原理给出了非线性度强弱的判定区间。通过仿真对比,验证了该非线性度量指标及其估计算法的有效性,并以磨煤机出口温度控制系统的非线性度量为例进行了实例仿真研究。
提出了评价线性高斯系统控制性能的最小信息熵基准,并将该基准推广到非线性非高斯系统。基于该基准定义了非线性非高斯系统的性能评价指标,进而给出非线性非高斯系统的性能评价方法。仿真对比验证了所提出性能指标和评价方法的有效性,并以磨煤机出口温度控制系统为例,研究了发电过程单回路控制系统的性能评价问题。
提出了一种基于线性解耦滤波的多变量控制系统性能评价方法。该方法可通过解耦滤波将多输入多输出系统转化多个单输入单输出系统进行评价,并给出各个回路对于系统整体性能的影响程度。在该评价方法的基础上,应用自举重采样方法实现了回路级的性能诊断。以火电机组汽轮机负荷转速多变量控制系统为例,对该方法的有效性进行了仿真验证。
Electric power relates the national economy and people's livelihood and is the source of social economy development. No matter traditional or new ways of generating energy power generation, the process of energy conversion to electrical energy goes through complex physical and chemical processes, and these processes often contain a large number of equipment and components.
In modern power plants, the control system is throughout the entire production process, and commands various equipment and components running automatically, and cooperatively in accordance with established specifications and operating procedures. With the increasing energy crisis and environmental problems, the control system further shoulders more functions in addition to the safe and stable operation. In this case, the performance of the control system will directly affect not only the running quality of the units but also the quality of output power.
This paper studies the control system performance evaluation in power generation process., the main contributions of this dissertation are given as following:
Nonlinearity is an important factor that affecting the control performance and the evaluation results. A nonlinearity measure based on minimum variance lower bound ratio is presented in this paper to qualify the nonlinear degree of closed loop systems. This measure is deduced from Hammerstein structure, but it also can be applied to Wiener structure and Wiener-Hammerstein structure. Besides, this measure can be estimated from the routine operating data. The threshold to judging whether nonlinearity is strong or weak is given by the principle of statistic interval. The effectiveness and consistency of this measure are illustrated by four simulations. The nonlinearity measure of coal mill outlet temperature control is given as an application example.
A minimum information entropy benchmark is proposed for assessing linear Guassian system and is extented to nonlinear non-Gaussian system. Then, a minimum information entropy based performance index is defined and the control performance assessment procedures are developed. Simulation tests and an industrial case study of coal mill outlet temperature control system are utilized to verify the effectiveness of the proposed procedures.
A new MIMO control system method based on output filtering is presented. This method can transform MIMO control performance assessment into multiple SISO control performance assessment by output filtering. The importance of every loop is obtained. With this CPA framework, a performance diagnosis method is presented with respect to the bootstrap resampling. The turbine load/speed control system is selected to test the effectiveness of the proposed procedures
引文
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