模糊预测控制在单元机组协调控制中的研究与应用
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摘要
大型火力发电厂的协调控制系统是一个典型的非线性、时变、多变量的控制系统。当前,国内外控制界都把复杂系统的控制作为控制科学与工程学科发展的前沿研究方向。本文主要研究了600MW机组协调控制系统的建模及先进控制策略,并结合了国电福州江阴发电有限公司#1机组的协调控制系统的设计、调试、投运及优化。采用模糊聚类的辨识方法建立单元机组负荷非线性模型;提出基于模糊模型的多变量广义预测控制方法,很好地解决单元机组大范围、快速变负荷的问题;针对目前参与AGC控制的火电机组存在响应速度慢等问题,提出了若干提高单元机组协调系统响应速度的方案,从而使机组能快速响应AGC负荷指令。
The coordinated control system (CCS) of turbine-generator unit is a typical nonlinear, time-varying, multi-variable control system. At present, the complex control system is regarded as the research direction of the control science and engineering disciplines development by the domestic and foreign-controlled experts. This paper studies the 600 MW Unit coordinated control system modeling and advanced control strategies, and the control system design, debugging, and optimization are applied in Fuzhou Jiangyin Power Company Limited, #1. Based on T-S fuzzy model, the unit load nonlinear model is established by using fuzzy clustering method. Based on the fuzzy model, the multivariable generalized predictive control method solves the large-scale, rapid load change problem. Automatic generation control (AGC) is an essential request of modern power system automatic control at present, slow response to AGC load demand is a serious problem existing in thermal power units taking part in AGC poor. The means of the improving the response to the unit CCS are applied the scheme, they assured the rapid response to AGC load demand of the power unit.
The coordinated control system (CCS) of turbine-generator unit is a typical nonlinear, time-varying, multi-variable control system. At present, the complex control system is regarded as the research direction of the control science and engineering disciplines development by the domestic and foreign-controlled experts. This paper studies the 600 MW Unit coordinated control system modeling and advanced control strategies, and the control system design, debugging, and optimization are applied in Fuzhou Jiangyin Power Company Limited, #1. Based on T-S fuzzy model, the unit load nonlinear model is established by using fuzzy clustering method. Based on the fuzzy model, the multivariable generalized predictive control method solves the large-scale, rapid load change problem. Automatic generation control (AGC) is an essential request of modern power system automatic control at present, slow response to AGC load demand is a serious problem existing in thermal power units taking part in AGC poor. The means of the improving the response to the unit CCS are applied the scheme, they assured the rapid response to AGC load demand of the power unit.
引文
[1]王东风,韩璞,曾德良.单元机组协调控制系统发展和现状[J].中国电力,2002,35(11):69～73
[2]Ramirez D.R. et. Al. Nonlinear MBPC for mobile robile robot nacigation using genetic algorithms. Proc. Of IEEE Int. Conf. On Robotcs&Automation. Detroit, Michigan, 1999: 2452～2457
[3]刘福才.非线性系统的模糊模型辨识及其应用.国防工业出版社,2006
[4]王伟.广义预测控制理论及其应用.科学出版社,1998
[5]Oliver Hacker et. al. Nonlinear system identification and predictive control of a heat exchange based on local fuzzy models. Proc. ACC, 1997, 3294～3298
[6]李少远,李柠.复杂系统的模糊预测控制及其应用.北京:科学出版社,2003
[7]朱红霞,沈炯,李益国.一种新的动态聚类算法及其在热工过程模糊建模中的应用.中国电机工程学报,2005,25(7)
[8]曾德良,刘吉臻.汽包锅炉的动态模型结构与负荷/压力增量预测模型[J].中国电机工程学报, 2000, 20(12): 75-79.
[9]韩忠旭,齐小红,潘钢等.本生直流炉机炉协调控制系统的设计新方法及其工程应用[J].中国电机工程学报, 2005,25(21):121-127
[10]席裕庚.预测控制.国防工业出版社,1991
[11]舒迪前.预测控制系统及其应用.机械工业出版社,1995
[12]曾海莹,刘暾东.模糊预测控制发展的概况.控制工程,2006
[13]Takagi T, Sugeno M. Fuzzy identification of systems and its application to control. IEEE Trans on SM C,1986,15(1):116～132
[14]房方,刘吉臻.单元机组协调系统的非线性控制研究[J].中国电力, 2004, 37(7): 61-65.
[15]张朝阳,李卫华,宋兆星.600MW超临界直流炉机组协调控制系统策略[J].华北电力技术,2007 ,1:24-28
[16]韩忠旭,齐小红,王擎,周广,常亚丽.协调控制系统快速响应AGC指令的设计新方法及其工程应用[J] .电网技术,2005,29(20):47-51
[17]王淼婺.火电机组协调控制对AGC的适应性分析[J] .中国电力,1999,32(6): 45-47
[18]朱北恒.火电厂热工自动化系统试验[M].北京:中国电力出版社,2006.
[19]朱红霞,沈炯,丁轲轲.单元机组负荷非线性预测控制及其仿真研究.中国电机工程学报,2006
[20]杨平,翁思义.连续时间广义预测控制用于电厂锅炉汽压控制的仿真研究.中国电机工程学报, 1993,13(1):50-55
[21]陈彦桥,刘吉臻,谭文,等.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[J].中国电机工程学报,2003,23(10):199-203.
[22]栾秀春,李士勇,吴建军,等.基于模糊状态观测器的单元机组T-S模糊协调控制系统[J].中国电机工程学报, 2006, 26(4):76-81.
[23]吕剑虹、陈来九、陈建勤,等.基于模糊规则的热工过程非线性模型的研究[J].中国电机工程学报, 2002, 22(11):132-137.
[24]华志刚、吕剑虹、张铁军.状态变量-预测控制技术在600MW机组再热汽温控制中的研究与应用[J].中国电机工程学报, 2005, 25(12)
[25]张强,李少远.基于遗传算法的约束广义预测控制.上海交通大学学报,2004,38(9)1562～1566
[26]Shin S.C. and Park S.B. GA-based predictive control for nonlinear processes. Electronics Letters, 1998, 34(20): 1980～1981
[27]Miguel Martinez, Juan S. Senent, Xavier Blasco. Generalized predictive control using genetic algorithms. Engineering Artificial Intelligence, 1998, 11: 355～367
[28]HAN Zhong-xu, LI Yue-feng, QIU Zhong-chang, ect. A new scheme of coordinated control system and its application in 600MW unit generator.in Proc. International Conference on Electrical Engineering 2005 (ICEE2005), CA1-03 ICEE-C0275.
[29]E.F. Camacho and C. Bordons, Model Predictive Control, Advanced Textbooks in Control and Signal Processing, Springer, London, 1999.
[30]J.A. Rossiter, Model-based Predictive Control---A practical Approach, CRC Press, 2003.
[31]Billings SA. Identification of nonlinear output-affine systems using an orthogonal least-squares algorithm. Int J Systems Sci, 1988, 19(8): 1559～1568
[32] Martin Fischer, Oliver Nelles, Rolf Isermann. Predictive control based on local linear fuzzy models. Int J Systems Sci,1998,29(7):679～697
[33]Clarke D W , Mohtadi C, Tuffs P S. Generalized predictive control-part I and II. Automatic, 1987,23(2):137～160
[34]Liu Haifa, WeiQingfu. Identification and optimization of T-S fuzzy model. In: Chen H F ed. Proceedings of the 14th World Congress of IFAC, Beijing, China, 1999;Pergamov: Elsevier Science, 1999,Vol K: 273～278
[35]Miyamoto S. Fuzzy Sets in Information Retrieval and Cluster Analysis. Boston: Kluwer Academic Publishers,1990
[36]Pedrycz W. An identification algorithm in fuzzy relational systems. Fuzzy Sets and Systems, 1984,13(2):153～167
[37]O.Bego, N.peric, I.Petrovic, decoupling multivariable GPC with reference observation.IEEE. 10th Mediterranean Electro technical Conference, M EleCon.2000, Vol.II: 819-82
[38]张化光.复杂系统的模糊辨识与模糊自适应控制.沈阳:东北大学出版社,1993
[2]Ramirez D.R. et. Al. Nonlinear MBPC for mobile robile robot nacigation using genetic algorithms. Proc. Of IEEE Int. Conf. On Robotcs&Automation. Detroit, Michigan, 1999: 2452～2457
[3]刘福才.非线性系统的模糊模型辨识及其应用.国防工业出版社,2006
[4]王伟.广义预测控制理论及其应用.科学出版社,1998
[5]Oliver Hacker et. al. Nonlinear system identification and predictive control of a heat exchange based on local fuzzy models. Proc. ACC, 1997, 3294～3298
[6]李少远,李柠.复杂系统的模糊预测控制及其应用.北京:科学出版社,2003
[7]朱红霞,沈炯,李益国.一种新的动态聚类算法及其在热工过程模糊建模中的应用.中国电机工程学报,2005,25(7)
[8]曾德良,刘吉臻.汽包锅炉的动态模型结构与负荷/压力增量预测模型[J].中国电机工程学报, 2000, 20(12): 75-79.
[9]韩忠旭,齐小红,潘钢等.本生直流炉机炉协调控制系统的设计新方法及其工程应用[J].中国电机工程学报, 2005,25(21):121-127
[10]席裕庚.预测控制.国防工业出版社,1991
[11]舒迪前.预测控制系统及其应用.机械工业出版社,1995
[12]曾海莹,刘暾东.模糊预测控制发展的概况.控制工程,2006
[13]Takagi T, Sugeno M. Fuzzy identification of systems and its application to control. IEEE Trans on SM C,1986,15(1):116～132
[14]房方,刘吉臻.单元机组协调系统的非线性控制研究[J].中国电力, 2004, 37(7): 61-65.
[15]张朝阳,李卫华,宋兆星.600MW超临界直流炉机组协调控制系统策略[J].华北电力技术,2007 ,1:24-28
[16]韩忠旭,齐小红,王擎,周广,常亚丽.协调控制系统快速响应AGC指令的设计新方法及其工程应用[J] .电网技术,2005,29(20):47-51
[17]王淼婺.火电机组协调控制对AGC的适应性分析[J] .中国电力,1999,32(6): 45-47
[18]朱北恒.火电厂热工自动化系统试验[M].北京:中国电力出版社,2006.
[19]朱红霞,沈炯,丁轲轲.单元机组负荷非线性预测控制及其仿真研究.中国电机工程学报,2006
[20]杨平,翁思义.连续时间广义预测控制用于电厂锅炉汽压控制的仿真研究.中国电机工程学报, 1993,13(1):50-55
[21]陈彦桥,刘吉臻,谭文,等.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[J].中国电机工程学报,2003,23(10):199-203.
[22]栾秀春,李士勇,吴建军,等.基于模糊状态观测器的单元机组T-S模糊协调控制系统[J].中国电机工程学报, 2006, 26(4):76-81.
[23]吕剑虹、陈来九、陈建勤,等.基于模糊规则的热工过程非线性模型的研究[J].中国电机工程学报, 2002, 22(11):132-137.
[24]华志刚、吕剑虹、张铁军.状态变量-预测控制技术在600MW机组再热汽温控制中的研究与应用[J].中国电机工程学报, 2005, 25(12)
[25]张强,李少远.基于遗传算法的约束广义预测控制.上海交通大学学报,2004,38(9)1562～1566
[26]Shin S.C. and Park S.B. GA-based predictive control for nonlinear processes. Electronics Letters, 1998, 34(20): 1980～1981
[27]Miguel Martinez, Juan S. Senent, Xavier Blasco. Generalized predictive control using genetic algorithms. Engineering Artificial Intelligence, 1998, 11: 355～367
[28]HAN Zhong-xu, LI Yue-feng, QIU Zhong-chang, ect. A new scheme of coordinated control system and its application in 600MW unit generator.in Proc. International Conference on Electrical Engineering 2005 (ICEE2005), CA1-03 ICEE-C0275.
[29]E.F. Camacho and C. Bordons, Model Predictive Control, Advanced Textbooks in Control and Signal Processing, Springer, London, 1999.
[30]J.A. Rossiter, Model-based Predictive Control---A practical Approach, CRC Press, 2003.
[31]Billings SA. Identification of nonlinear output-affine systems using an orthogonal least-squares algorithm. Int J Systems Sci, 1988, 19(8): 1559～1568
[32] Martin Fischer, Oliver Nelles, Rolf Isermann. Predictive control based on local linear fuzzy models. Int J Systems Sci,1998,29(7):679～697
[33]Clarke D W , Mohtadi C, Tuffs P S. Generalized predictive control-part I and II. Automatic, 1987,23(2):137～160
[34]Liu Haifa, WeiQingfu. Identification and optimization of T-S fuzzy model. In: Chen H F ed. Proceedings of the 14th World Congress of IFAC, Beijing, China, 1999;Pergamov: Elsevier Science, 1999,Vol K: 273～278
[35]Miyamoto S. Fuzzy Sets in Information Retrieval and Cluster Analysis. Boston: Kluwer Academic Publishers,1990
[36]Pedrycz W. An identification algorithm in fuzzy relational systems. Fuzzy Sets and Systems, 1984,13(2):153～167
[37]O.Bego, N.peric, I.Petrovic, decoupling multivariable GPC with reference observation.IEEE. 10th Mediterranean Electro technical Conference, M EleCon.2000, Vol.II: 819-82
[38]张化光.复杂系统的模糊辨识与模糊自适应控制.沈阳:东北大学出版社,1993