组态化预测控制及其在脱硫pH值控制中的仿真研究
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摘要
为进一步提高火电机组脱硫系统的控制品质,用广义预测控制器替代传统脱硫pH值串级控制主调比例微分积分(PID)控制器,并通过算法简化与函数拟合提出了一种组态化预测控制方法,基于该算法通过集散控制系统(DCS)组态设计脱硫pH值控制系统。结果表明:组态化预测控制对pH值的控制在调节时间、超调量及动态偏差等方面均优于传统串级PID控制,可显著提高pH值的调节精度同时降低调节时间;与常规广义预测控制相比,组态化预测控制的控制性能基本相同。
To further improve the control quality upon desulfurization systems of thermal power units, a generalized predictive controller was used to replace the traditional primary PID controller for pH value cascade control of the desulfurization systems. Meanwhile, a configuration predictive control method was proposed by simplifying the algorithm and fitting the functions, based on which, a new pH value control system was designed through DCS configuration. Results show that the configuration predictive controller is superior to traditional cascade controller in terms of adjustment time, overshoot and dynamic deviation, which can significantly improve the adjustment accuracy and reduce the adjustment time on pH values. Compared with conventional generalized predictive controller, the configuration predictive controller has basically the same control performance.
To further improve the control quality upon desulfurization systems of thermal power units, a generalized predictive controller was used to replace the traditional primary PID controller for pH value cascade control of the desulfurization systems. Meanwhile, a configuration predictive control method was proposed by simplifying the algorithm and fitting the functions, based on which, a new pH value control system was designed through DCS configuration. Results show that the configuration predictive controller is superior to traditional cascade controller in terms of adjustment time, overshoot and dynamic deviation, which can significantly improve the adjustment accuracy and reduce the adjustment time on pH values. Compared with conventional generalized predictive controller, the configuration predictive controller has basically the same control performance.
引文
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[15] AFRAM A,JANABI-SHARIFI F.Theory and applications of HVAC control systems—a review of model predictive control (MPC)[J].Building and Environment,2014,72:343-355.
[16] 张重阳,何小刚,张成.燃煤火电厂提高浆液脱硫效率PH值控制仿真[J].计算机仿真,2017,34(9):109-113.ZHANG Chongyang,HE Xiaogang,ZHANG Cheng.PH value control simulation of improving slurry desulfurization efficiency in coal-fired power plant[J].Computer Simulation,2017,34(9):109-113.
[2] 陈浩,骆仲泱,江建平,等.电厂湿法烟气脱硫颗粒物排放特性的实验研究[J].动力工程学报,2017,37(11):925-930,937.CHEN Hao,LUO Zhongyang,JIANG Jianping,et al.Experimental study on emission characteristics of particulate matters from wet flue gas desulfurization system of a coal-fired power plant[J].Journal of Chinese Society of Power Engineering,2017,37(11):925-930,937.
[3] 崔仕文,铁治欣,丁成富,等.基于偏最小二乘支持向量机的烟气湿法脱硫效率预测模型[J].热力发电,2017,46(4):81-87.CUI Shiwen,TIE Zhixin,DING Chengfu,et al.Prediction model for flue gas wet desulfurization efficiency based on partial least squares support vector machine[J].Thermal Power Generation,2017,46(4):81-87.
[4] 王楠,贠卫国,王冰.DCS在2×660 MW机组脱硫控制系统中的应用与分析[J].化工自动化及仪表,2015,42(7):818-822,837.WANG Nan,YUN Weiguo,WANG Bing.DCS analysis and application in 2×660 MW power unit desulfurization[J].Control and Instruments in Chemical Industry,2015,42(7):818-822,837.
[5] 宋涛,吴周晶,邱寅祺.超超临界机组脱硫系统优化[J].锅炉技术,2015,46(增刊1):62-65.SONG Tao,WU Zhoujing,QIU Yinqi.The optimizes of desulfurization for ultra-supercritical unit[J].Boiler Technology,2015,46(Sup1):62-65.
[6] 李洁,刘晋宁.锅炉烟气脱硫系统中pH值的控制与实现[J].化工自动化及仪表,2014,41(8):905-906,942.LI Jie,LIU Jinning.pH value control and implementation in boiler flue gas desulfurization system[J].Control and Instruments in Chemical Industry,2014,41(8):905-906,942.
[7] 李骏,沈凯,周长城,等.烟气脱硫吸收塔pH值控制策略优化研究[J].环境科学与技术,2012,35(4):43-46.LI Jun,SHEN Kai,ZHOU Changcheng,et al.Optimization for pH value control of flue gas desulphurization tower[J].Environmental Science & Technology,2012,35(4):43-46.
[8] 辛玲玲,张建江,周水琴.自动控制技术在火电厂烟气湿法脱硫中的应用[J].中国电力,2007,40(8):75-78.XIN Lingling,ZHANG Jianjiang,ZHOU Shuiqin.Application of automatic control technology in the wet FGD of thermal power plant[J].Electric Power,2007,40(8):75-78.
[9] 邹平.烟气脱硫工艺中PH值控制策略研究与应用[D].北京:华北电力大学,2013.
[10] 付文秀.大型脱硫系统的建模与优化控制方法的研究与应用[D].保定:华北电力大学,2015.
[11] 薛美盛,陶呈纲,郑涛.pH值控制策略研究[J].化工自动化及仪表,2009,36(5):7-12,17.XUE Meisheng,TAO Chenggang,ZHENG Tao.Research on pH control strategies[J].Control and Instruments in Chemical Industry,2009,36(5):7-12,17.
[12] CLARKE D W,MOHTADI C,TUFFS P S.Generalized predictive control—part I.The basic algorithm[J].Automatica,1987,23(2):137-148.
[13] HOLKAR K S,WAGHMARE L M.An overview of model predictive control[J].International Journal of Control and Automation,2010,3(4):47-63.
[14] VAZQUEZ S,LEON J I,FRANQUELO L G,et al.Model predictive control:a review of its applications in power electronics[J].IEEE Industrial Electronics Magazine,2014,8(1):16-31.
[15] AFRAM A,JANABI-SHARIFI F.Theory and applications of HVAC control systems—a review of model predictive control (MPC)[J].Building and Environment,2014,72:343-355.
[16] 张重阳,何小刚,张成.燃煤火电厂提高浆液脱硫效率PH值控制仿真[J].计算机仿真,2017,34(9):109-113.ZHANG Chongyang,HE Xiaogang,ZHANG Cheng.PH value control simulation of improving slurry desulfurization efficiency in coal-fired power plant[J].Computer Simulation,2017,34(9):109-113.
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