单元机组协调控制研究
摘要
作为单元机组的主控系统,协调控制系统对于机组运行的安全性、经济性及机组的调峰、调频能力都有直接影响,因此设计有效的火电厂单元机组协调控制系统是提高热工自动化水平的关键问题。随着智能控制理论和应用研究的逐步深入,其在协调控制系统设计中也得到广泛关注。尽管大多数方法仍处于仿真试验阶段,其研究深度及算法的实用性还不及常规理论,但作为能解决大范围、全工况优化运行的控制方案,智能控制策略的研究为协调控制系统的设计提供了很好的研究方向。
本文主要分析了目前协调控制系统的发展现状、研究成果以及存在的一些问题,通过广泛的选择和比较,确定了300MW机组100%和70%工况点下线性模型以及330MW机组90%负荷工况点下非线性模型。这些模型结构简单、特征突出,具有代表性,适用于协调控制系统的设计与仿真。本文通过对常规PID协调控制器设计方法地整理,针对上述模型进行了常规PID协调控制系统的设计,并在对模糊控制理论,神经网络理论较为深入研究的基础之上,设计了模糊自适应PID协调控制器、单神经元PID协调控制器、改进DRNN神经网络PID协调控制器,并分别与常规PID协调控制器进行了对比研究,并分析了各个智能PID控制器应用于单元机组对象的特点。
As the main control system of unit, coordinated control system has a direct impact on unit operating security, economy and the ability of unit peaking load and holding frequency, so the key issues to improve the Thermal automation level is designing a effective coordinated control system of the power unit. With the depth research on intelligent control theory and application, it has been widespread concern in the coordinated control system designing. Although the majority of methods are still in simulating and testing stage and its research depth and algorithm practicality are less than the conventional theory,the study of intelligent control strategy provide a good direction. for coordinated control system design.
The current development, study results and some existence of problems of coordinated control system are analysed in this paper. Through comprehensively chosen and compared, the linear models of 300MW unit in 70% and 100% operating mode and the non-linear model of 330MW unit in 90% operating mod are identified. These models have simple structure, prominent feature and are representative, so they are applicable to designing and simulation of the coordination control system. Arranging the designing method of convention PID coordination controller, the convention PID coordination control system for the models have been designed. Through indepth study on the Fuzzy control theory, neural network theory, Fuzzy self-adaptive PID coordination controller, single neural PID coordination controller, modified diagonal recurrent neural network(DRNN) PID coordination controller have been designed, and these study results are compared to convention PID coordination controller. Depending on this comparison, this paper analyses characteristics of these intelligent controllers which apply to the unit.
本文主要分析了目前协调控制系统的发展现状、研究成果以及存在的一些问题,通过广泛的选择和比较,确定了300MW机组100%和70%工况点下线性模型以及330MW机组90%负荷工况点下非线性模型。这些模型结构简单、特征突出,具有代表性,适用于协调控制系统的设计与仿真。本文通过对常规PID协调控制器设计方法地整理,针对上述模型进行了常规PID协调控制系统的设计,并在对模糊控制理论,神经网络理论较为深入研究的基础之上,设计了模糊自适应PID协调控制器、单神经元PID协调控制器、改进DRNN神经网络PID协调控制器,并分别与常规PID协调控制器进行了对比研究,并分析了各个智能PID控制器应用于单元机组对象的特点。
As the main control system of unit, coordinated control system has a direct impact on unit operating security, economy and the ability of unit peaking load and holding frequency, so the key issues to improve the Thermal automation level is designing a effective coordinated control system of the power unit. With the depth research on intelligent control theory and application, it has been widespread concern in the coordinated control system designing. Although the majority of methods are still in simulating and testing stage and its research depth and algorithm practicality are less than the conventional theory,the study of intelligent control strategy provide a good direction. for coordinated control system design.
The current development, study results and some existence of problems of coordinated control system are analysed in this paper. Through comprehensively chosen and compared, the linear models of 300MW unit in 70% and 100% operating mode and the non-linear model of 330MW unit in 90% operating mod are identified. These models have simple structure, prominent feature and are representative, so they are applicable to designing and simulation of the coordination control system. Arranging the designing method of convention PID coordination controller, the convention PID coordination control system for the models have been designed. Through indepth study on the Fuzzy control theory, neural network theory, Fuzzy self-adaptive PID coordination controller, single neural PID coordination controller, modified diagonal recurrent neural network(DRNN) PID coordination controller have been designed, and these study results are compared to convention PID coordination controller. Depending on this comparison, this paper analyses characteristics of these intelligent controllers which apply to the unit.
引文
[1] 赵志强,秦义.火力发电机组协调控制系统浅析.东北电力技术,2002, 11: 9~41.
[2] 于达仁,翁一武,王仲奇.火电单元机组的柔性控制. 中国电机工程学报,2002,22(7):129-133.
[3] 焦海锋,张利生,李进荣.分散控制系统在机炉协调控制中的应用. 电力学报, 2005,20(4):372~374.
[4] 刘文林,张晓辉.几种协调控制系统控制方案分析.东北电力技术, 2001, 5:48~49.
[5] Chen K W, Asok R. Robust Wide-Range Control of Stream-Electric Power Plants. IEEE Transactions on Control Systems Technology, 1997, 5(1): 74-88.
[6] 田亮,刘鑫屏,于希宁.一种协调控制系统参数的鲁棒整定方法.热能动力工程,2006,1(21):84~87.
[7] 郑亚锋,陈彦桥,卫平宝.基于模糊多模型 330MW 单元机组协调控制系统.电力系统及其自动化学报,2006,2(18):71~74.
[8] 陈彦桥,刘吉臻,谭 文. 模糊多模型控制及其对 500MW 单元机组协 调控制系统的仿真研究.中国电机工程学报, 2003, 10(23): 1611 ~ 1613.
[9] 侯国莲,李 泉,张建华.变论域自适应模糊滑模多变量控制算法及其在单元机组协调控制中的应用.中国电机工程学报,2005, 9 (25) :114~121.
[10] 张建华,董菲,侯国莲.基于神经网络预测控制的单元机组协调控制策略.动力工程,2006,3(26):392~395.
[11] 张建明,王宁,王树青.火电单元机组的模糊神经元协调控制.动力工程, 1999,3(19):38~42.
[12] 张建明,王宁,王树青.火力单元机组的前馈模糊神经非模型协调控制. 动力工程,2000,3(20):664~668.
[13] 黄湘云,朱学峰.预测控制的研究现状与展望.石油化工自动化. 2005,2(2) 27~31.
[14] 贾青.多变量分散型预测控制应用研究.化工自动化及仪表,2000, 27:1~4.
[15] 王东风.多变量系统的广义预测控制解耦设计.电机与控制学报,2000, 4(4):243~246.
[16] 李玉红,王东风,刘红军.机炉协调系统的动态矩阵控制仿真研究.电力科学与工程,2004,4:11~14.
[17] 侯国莲,吴春芳,张建华.多变量混合预测算法在单元机组协调控制中的应用.现代电力,2004,6(21):15~18.
[18] Hogg B W,Ei-Rabaie N M.Generalized predictive control of steam pressure in a drum boiler.IEEE Transactions on Energy Conversion, 1990,5(3):485~492.
[19] Hogg B W, Ei-Rabaie N M. Multivariable generalized predictive control of a boiler system.IEEE Transactions on Energy Conversion, 1994, 6(2):282~288.
[20] Lu S, Hogg B W. Predictive coordinated control for power-plant steam pressure and power output. Control eng. Practice, 1997, 5(1):79~84.
[21] Prasad G, Irwin G W, Swidenbank E, Hogg B W.plant-wide predictive control for a thermal power plant based on physica plant model. IEEE Proceedings-Control Theory and Applications, 2000, 147(5):523~ 537.
[22] Richalet J, Abuels, Ata-Doss. Predictive functional control: Application to fast and acctate robots. Proceeding of IFAC 10th world Congress, Munich. 2003:2785~2790.
[23] 侯国莲,刘洋,张建华.预测函数控制在火电厂单元机组协调控制系统中的应用.中国动力工程学报,2005,2(25):239~243.
[24] 刘吉臻.协调控制与给水全过程控制.北京,中国电力出版社,1995.
[25] 房方.单元机组协调控制系统的先进控制策略研究.北京:华北电力大学,2005.
[26] 吴国垣,李东海,薛亚丽.机炉协调控制的分散 PID 整定.清华大学学报(自然科学版),2004,2(44):262~265.
[27] 房方,刘吉臻,谭文. 火电单元机组协调控制系统的多变量 IMC2PID 设计. 动力工程,2004,3(24):360~365.
[28] 窦振中.模糊逻辑控制技术及其应用.北京:北京航空航天大学出版社,1995.
[29] 张曾科.模糊数学在自动化技术中的应用.北京:清华大学出版社, 1997.
[30] 罗光明,黄晓宇,朱建林. 基于 MATLAB 的模糊自整定 PID 参数控制器计算机仿真.机械与电子.2001(2).
[31] 赵玮 , 谭德荣 , 于剑峰 .SIMULINK 中自定义模块的创建 . 微计算机应用,2006,23(4):379~381.
[32] 田亮,曾德良,刘吉臻等.简化的 330MW 机组非线性动态模型.中国电机工程学报,2004,24(8):180~184.
[33] 周黎辉.神经网络在过程辨识与控制中的应用研究.北京:华北电力大学, 2003.
[34] 舒怀林. PID 神经元网络及其控制系统.北京.国防工业出版社, 2006.
[35] Ku Chao-Chee,Lee Kwang.Diagonal recurrent neural networks for dynamic system control. IEEE, Transaction on Neural Networks. 1995, 6(1):144~156.
[36] 刘红军,韩璞,于希宁.基于对角递归神经网络整定的 PID 解耦单元机组负荷控制系统.动力工程,2004,24(6):809~812.
[37] 杨青,党选举.基于 DRNN 的多变量解耦控制系统.自动化技术与应用, 2004,23(3):14~17.
[38] 谭永红,党选举,范·高温伯格,迈达德·萨义夫. 用 PID 梯度算法训练基于神经网络的广义非线性 PID 控制器(英文).控制理论与应用. 2000,17(6):861~867.
[39] 焦李成.神经网络的应用与实现.西安:西安电子科技大学出版社,1993.
[40] 何玉彬,李新忠.神经网络控制技术及其应用.北京:科学出版社,2000.
[41] Liu H B, Li S Y, Chai T Y. Intelligent decoupling control of power plant steam pressure and power output.Electtrical Power and Energy System, 2003,25:809~819.
[42] Tan W, Liu J Z, Fang F. Tuning of PID controllers for boiler-turbine units . ISA Transactions,2004,43(4):571~583.
[43] 邱华 ,蔡军 .单元机组负荷控制的专家协调控制 .华北电力技术 , 2000, 5(13) :20~23.
[44] 王晓哲,李界家,吴成东.多变量系统解耦方法综述.沈阳建筑工程学院学报,2000,12(16):143~145.
[45] 胡智奇,王印松. H∞控制方法及研究现状.电力情报,2000,3:5~7.
[46] 田亮.单元机组非线性动态模型的研究.北京:华北电力大学,2005.
[47] 张华磊.神经网络-模糊控制在协调控制系统中的应用.北京:华北电力大学,2004.
[48] Chai Tianyou, Wang Xin, Yue Heng. Multivariable Intelligent Decoupling Control and Its Applications. Proceedings of the 3nd World Congress on Intelligent Control and Automation, June 28-July 2, 2000. Hefei, China.
[49] Le Wei, Fang Fang. Structure Optimization Based on Nonlinear Methods for the Coordinated Control System of Power Units. Proceedings of the 6th World Congress on Intelligent Control and Automation, June 21~23, 2006, Dalian, China.
[50] 刘金琨.先进 P I D 控制及其 MATLAB 仿真.北京:电子工业出版社,2003.
[51] 柴天佑.多变量自适应解耦控制及应用.北京:科学出版社,2001.
[2] 于达仁,翁一武,王仲奇.火电单元机组的柔性控制. 中国电机工程学报,2002,22(7):129-133.
[3] 焦海锋,张利生,李进荣.分散控制系统在机炉协调控制中的应用. 电力学报, 2005,20(4):372~374.
[4] 刘文林,张晓辉.几种协调控制系统控制方案分析.东北电力技术, 2001, 5:48~49.
[5] Chen K W, Asok R. Robust Wide-Range Control of Stream-Electric Power Plants. IEEE Transactions on Control Systems Technology, 1997, 5(1): 74-88.
[6] 田亮,刘鑫屏,于希宁.一种协调控制系统参数的鲁棒整定方法.热能动力工程,2006,1(21):84~87.
[7] 郑亚锋,陈彦桥,卫平宝.基于模糊多模型 330MW 单元机组协调控制系统.电力系统及其自动化学报,2006,2(18):71~74.
[8] 陈彦桥,刘吉臻,谭 文. 模糊多模型控制及其对 500MW 单元机组协 调控制系统的仿真研究.中国电机工程学报, 2003, 10(23): 1611 ~ 1613.
[9] 侯国莲,李 泉,张建华.变论域自适应模糊滑模多变量控制算法及其在单元机组协调控制中的应用.中国电机工程学报,2005, 9 (25) :114~121.
[10] 张建华,董菲,侯国莲.基于神经网络预测控制的单元机组协调控制策略.动力工程,2006,3(26):392~395.
[11] 张建明,王宁,王树青.火电单元机组的模糊神经元协调控制.动力工程, 1999,3(19):38~42.
[12] 张建明,王宁,王树青.火力单元机组的前馈模糊神经非模型协调控制. 动力工程,2000,3(20):664~668.
[13] 黄湘云,朱学峰.预测控制的研究现状与展望.石油化工自动化. 2005,2(2) 27~31.
[14] 贾青.多变量分散型预测控制应用研究.化工自动化及仪表,2000, 27:1~4.
[15] 王东风.多变量系统的广义预测控制解耦设计.电机与控制学报,2000, 4(4):243~246.
[16] 李玉红,王东风,刘红军.机炉协调系统的动态矩阵控制仿真研究.电力科学与工程,2004,4:11~14.
[17] 侯国莲,吴春芳,张建华.多变量混合预测算法在单元机组协调控制中的应用.现代电力,2004,6(21):15~18.
[18] Hogg B W,Ei-Rabaie N M.Generalized predictive control of steam pressure in a drum boiler.IEEE Transactions on Energy Conversion, 1990,5(3):485~492.
[19] Hogg B W, Ei-Rabaie N M. Multivariable generalized predictive control of a boiler system.IEEE Transactions on Energy Conversion, 1994, 6(2):282~288.
[20] Lu S, Hogg B W. Predictive coordinated control for power-plant steam pressure and power output. Control eng. Practice, 1997, 5(1):79~84.
[21] Prasad G, Irwin G W, Swidenbank E, Hogg B W.plant-wide predictive control for a thermal power plant based on physica plant model. IEEE Proceedings-Control Theory and Applications, 2000, 147(5):523~ 537.
[22] Richalet J, Abuels, Ata-Doss. Predictive functional control: Application to fast and acctate robots. Proceeding of IFAC 10th world Congress, Munich. 2003:2785~2790.
[23] 侯国莲,刘洋,张建华.预测函数控制在火电厂单元机组协调控制系统中的应用.中国动力工程学报,2005,2(25):239~243.
[24] 刘吉臻.协调控制与给水全过程控制.北京,中国电力出版社,1995.
[25] 房方.单元机组协调控制系统的先进控制策略研究.北京:华北电力大学,2005.
[26] 吴国垣,李东海,薛亚丽.机炉协调控制的分散 PID 整定.清华大学学报(自然科学版),2004,2(44):262~265.
[27] 房方,刘吉臻,谭文. 火电单元机组协调控制系统的多变量 IMC2PID 设计. 动力工程,2004,3(24):360~365.
[28] 窦振中.模糊逻辑控制技术及其应用.北京:北京航空航天大学出版社,1995.
[29] 张曾科.模糊数学在自动化技术中的应用.北京:清华大学出版社, 1997.
[30] 罗光明,黄晓宇,朱建林. 基于 MATLAB 的模糊自整定 PID 参数控制器计算机仿真.机械与电子.2001(2).
[31] 赵玮 , 谭德荣 , 于剑峰 .SIMULINK 中自定义模块的创建 . 微计算机应用,2006,23(4):379~381.
[32] 田亮,曾德良,刘吉臻等.简化的 330MW 机组非线性动态模型.中国电机工程学报,2004,24(8):180~184.
[33] 周黎辉.神经网络在过程辨识与控制中的应用研究.北京:华北电力大学, 2003.
[34] 舒怀林. PID 神经元网络及其控制系统.北京.国防工业出版社, 2006.
[35] Ku Chao-Chee,Lee Kwang.Diagonal recurrent neural networks for dynamic system control. IEEE, Transaction on Neural Networks. 1995, 6(1):144~156.
[36] 刘红军,韩璞,于希宁.基于对角递归神经网络整定的 PID 解耦单元机组负荷控制系统.动力工程,2004,24(6):809~812.
[37] 杨青,党选举.基于 DRNN 的多变量解耦控制系统.自动化技术与应用, 2004,23(3):14~17.
[38] 谭永红,党选举,范·高温伯格,迈达德·萨义夫. 用 PID 梯度算法训练基于神经网络的广义非线性 PID 控制器(英文).控制理论与应用. 2000,17(6):861~867.
[39] 焦李成.神经网络的应用与实现.西安:西安电子科技大学出版社,1993.
[40] 何玉彬,李新忠.神经网络控制技术及其应用.北京:科学出版社,2000.
[41] Liu H B, Li S Y, Chai T Y. Intelligent decoupling control of power plant steam pressure and power output.Electtrical Power and Energy System, 2003,25:809~819.
[42] Tan W, Liu J Z, Fang F. Tuning of PID controllers for boiler-turbine units . ISA Transactions,2004,43(4):571~583.
[43] 邱华 ,蔡军 .单元机组负荷控制的专家协调控制 .华北电力技术 , 2000, 5(13) :20~23.
[44] 王晓哲,李界家,吴成东.多变量系统解耦方法综述.沈阳建筑工程学院学报,2000,12(16):143~145.
[45] 胡智奇,王印松. H∞控制方法及研究现状.电力情报,2000,3:5~7.
[46] 田亮.单元机组非线性动态模型的研究.北京:华北电力大学,2005.
[47] 张华磊.神经网络-模糊控制在协调控制系统中的应用.北京:华北电力大学,2004.
[48] Chai Tianyou, Wang Xin, Yue Heng. Multivariable Intelligent Decoupling Control and Its Applications. Proceedings of the 3nd World Congress on Intelligent Control and Automation, June 28-July 2, 2000. Hefei, China.
[49] Le Wei, Fang Fang. Structure Optimization Based on Nonlinear Methods for the Coordinated Control System of Power Units. Proceedings of the 6th World Congress on Intelligent Control and Automation, June 21~23, 2006, Dalian, China.
[50] 刘金琨.先进 P I D 控制及其 MATLAB 仿真.北京:电子工业出版社,2003.
[51] 柴天佑.多变量自适应解耦控制及应用.北京:科学出版社,2001.