烧结烟气脱硫过程塔顶温度智能控制策略及工业应用
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摘要
钢铁行业二氧化硫排放量约占全国工业二氧化硫排放总量的8%,仅次于火电行业,位居第二位。钢铁行业排放的二氧化硫主要是烧结(球团)工序产生的,因此烧结烟气脱硫在钢铁行业节能减排中占重要地位。在烧结循环流化床烟气脱硫工艺中,塔顶温度稳定控制对提高脱硫效率具有重要意义。然而,喷水减温是一个复杂的工业过程,具有非线性、时滞、大扰动等控制难点。如何实现塔顶温度的稳定控制,是实现提高脱硫效率的关键性问题。
本文在分析循环流化床烟气脱硫工艺的基础上,总结出塔顶温度的控制难点。通过应用智能控制理论,提出了一种基于动态矩阵预测结合前馈补偿控制的塔顶温度智能控制策略,实现了塔顶温度的稳定控制。
首先,针对喷水减温过程的惯性、时滞特性,应用自回归模型(ARX)描述喷水减温过程,并采用最小二乘法辨识模型。然后利用该模型的阶跃响应系数建立塔顶温度动态矩阵预测控制器的预测模型,并设计控制器参数。为了解决预测控制中模型失配的问题,采用模糊在线校正的方法,实现在线闭环校正的功能。同时,为了抑制扰动波动对系统的影响,采用前馈补偿的方法,将前馈和反馈的控制方式相结合,当扰动因素发生变化时,通过前馈模型进行补偿调节。实验仿真过程中,以建立的ARX模型为对象,仿真实验验证了本文所提出的控制策略的有效性。
为了验证控制算法实际应用价值,针对国内某大型钢铁企业的循环流化床烟气脱硫系统,开发塔顶温度控制系统。运行结果表明：该系统实现了塔顶温度的稳定控制,有效抑制了扰动对系统造成的影响,提高了脱硫效率。
Steel industry accounts for about 8% of the world's SO2 emissions, which is second to coal fire industry. Sintering is a process producing the largest amounts of SO2 in the steel industry, therefore sintering flue gas desulfurization plays an important part in energy conservation and emission reduction of steel industry. In the mechanism of circulating fluidized bed, stabilizing tower top temperature is significant to improving efficiency of desulfurization. However, spray desuperheating is a complex process with time-delay, time-varying and disturbance. How to control tower top temperature is the key to improve efficiency of desulfurization.
On the basis of analyzing the mechanism of CFB flue gas desulfurization, this paper summarized the main problems in tower top temperature control. By using intelligent control theory, an intelligent control strategy, which combines dynamic matrix control with feedforward compensation control, is proposed to achieve the stability of tower top temperature.
First, according to the inertia and time-delay of spray desuperheating, an auto regressive with external model is used to describe this process, and identified by using least square method. A predictive model of dynamic matrix controller is established based on the step responsive coefficient. Then, to achieve the function of correction on-line, fuzzy correct control is adopted to solve the problem of model mismatch. Meantime, in order to suppress the influence of the disturbances, a compensating feedforward model is added to the system. According to the model's calculations, compensation value is computed while the disturbance changes. Simulations, based on the ARX model, verify.the effectiveness of the strategy proposed in this paper.
To verify its value of practical application, in 360m2 sintering factory of an iron and steel enterprise, tower top temperature intelligent control is developed based on the original control system of CFB in an iron and steel enterprise. The running results shows that the system can stabilize the tower top temperature, suppress the influence of the disturbances and improve the efficiency of desulfurization.
本文在分析循环流化床烟气脱硫工艺的基础上,总结出塔顶温度的控制难点。通过应用智能控制理论,提出了一种基于动态矩阵预测结合前馈补偿控制的塔顶温度智能控制策略,实现了塔顶温度的稳定控制。
首先,针对喷水减温过程的惯性、时滞特性,应用自回归模型(ARX)描述喷水减温过程,并采用最小二乘法辨识模型。然后利用该模型的阶跃响应系数建立塔顶温度动态矩阵预测控制器的预测模型,并设计控制器参数。为了解决预测控制中模型失配的问题,采用模糊在线校正的方法,实现在线闭环校正的功能。同时,为了抑制扰动波动对系统的影响,采用前馈补偿的方法,将前馈和反馈的控制方式相结合,当扰动因素发生变化时,通过前馈模型进行补偿调节。实验仿真过程中,以建立的ARX模型为对象,仿真实验验证了本文所提出的控制策略的有效性。
为了验证控制算法实际应用价值,针对国内某大型钢铁企业的循环流化床烟气脱硫系统,开发塔顶温度控制系统。运行结果表明：该系统实现了塔顶温度的稳定控制,有效抑制了扰动对系统造成的影响,提高了脱硫效率。
Steel industry accounts for about 8% of the world's SO2 emissions, which is second to coal fire industry. Sintering is a process producing the largest amounts of SO2 in the steel industry, therefore sintering flue gas desulfurization plays an important part in energy conservation and emission reduction of steel industry. In the mechanism of circulating fluidized bed, stabilizing tower top temperature is significant to improving efficiency of desulfurization. However, spray desuperheating is a complex process with time-delay, time-varying and disturbance. How to control tower top temperature is the key to improve efficiency of desulfurization.
On the basis of analyzing the mechanism of CFB flue gas desulfurization, this paper summarized the main problems in tower top temperature control. By using intelligent control theory, an intelligent control strategy, which combines dynamic matrix control with feedforward compensation control, is proposed to achieve the stability of tower top temperature.
First, according to the inertia and time-delay of spray desuperheating, an auto regressive with external model is used to describe this process, and identified by using least square method. A predictive model of dynamic matrix controller is established based on the step responsive coefficient. Then, to achieve the function of correction on-line, fuzzy correct control is adopted to solve the problem of model mismatch. Meantime, in order to suppress the influence of the disturbances, a compensating feedforward model is added to the system. According to the model's calculations, compensation value is computed while the disturbance changes. Simulations, based on the ARX model, verify.the effectiveness of the strategy proposed in this paper.
To verify its value of practical application, in 360m2 sintering factory of an iron and steel enterprise, tower top temperature intelligent control is developed based on the original control system of CFB in an iron and steel enterprise. The running results shows that the system can stabilize the tower top temperature, suppress the influence of the disturbances and improve the efficiency of desulfurization.
引文
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[2]中华人民共和国工业和信息化部.关于印发钢铁行业烧结烟气脱硫实施方案的通知.工信部节[2009]340号.
[3]陈健.烧结烟气脱硫方式的分析探讨.世界钢铁,2010,(3)：1-6.
[4]吴复忠,李军旗,金会心.烧结烟气脱硫技术现状分析.工业加热,2008,37(5)：1-3.
[5]惠远峰.石灰石-石膏法烟气脱硫系统设计.工业安全与环保,2009,35(9)：12-14.
[6]刘征建,张建良,杨天钧.烧结烟气脱硫技术的研究与发展.中国冶金,2009,19(2)：1-5.
[7]党玉华,齐渊洪,王海风.烧结烟气脱硫技术.钢铁研究学报,2010,22(5)：1-6.
[8]J. Zhang, C. F. You, H. Y. Qi, C. G. Chen, X. C. Xu. Effect of operating parameters and reactor structure on moderate temperature dry desulfurization. Environmental Science and Technology,2006,40 (13):4300-4305.
[9]国家统计局编.中国统计年鉴.北京：中国统计出版社,2000-2010.
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[11]高继慧,马春元,吴少华等.半干式脱硫系统的热量物质衡算模型.热能动力工程,2001,16(5)：530-532.
[12]Q. H. Wang, Z. Y. Luo, X. T. Li, M. Q. Fang, M. Q. L. Ni, K. Cen. A mathematical model for a circulating fluidized bed (CFB) boiler. Energy,1999, 24 (7):633-653.
[13]A. Gungor, N. Eskin. Two-dimensional coal combustion modeling of CFB. International Journal of Thermal Sciences,2008,47 (2):157-174.
[14]N. Matsushima, Y. Li, M. Nishioka, M. Sadakata, H. Y. Qi and X. C. Xu. Novel dry-desulfurization process using Ca(OH)2 /fly ash sorbent in a circulating fluidized bed. Environmental Science and Technology,2004,38 (24):6867-6874.
[15]F. F. Hill, J. Zank. Flue gas desulphurization by spray dry absorption. Chemical Engineering Processing,2000,39 (1):45-52.
[16]F. Scala, M. D'Ascenzo, A. Lancia. Modeling flue gas desulfurization by spray-dry absorption. Separation and Purification Technology,2004,34 (1-3): 143-153.
[17]陶树成,高自强,陆万鹏等.某热电厂循环流化床锅炉降低排烟温度的技术措施探讨.电力技术,2010,(2)：62-66.
[18]赵果然.循环流化床锅炉国内外现状概述.锅炉制造,2009,(4)：19-21.
[19]程乐鸣.大型循环流化床锅炉的发展.动力工程,2008,28(6)：817-826.
[20]余志杰.福建三钢180m2烧结机烟气循环流化床干法脱硫装置.能源与环境,2008,(4)：66-68.
[21]李希昌,周玉春.烧结烟气脱硫技术比较浅析.能源与环境,2010,(4)：102-103.
[22]A. K. Das, J. D. Wilde, G. J. Heynderickx, G. B. Marin. Simultaneous adsorption of SO2-NOX from flue gases in a riser configuration. American Institute of Chemical Engineers Journal,2001,47 (12):2831-2844.
[23]A. Gomez, N. Fueyo, A. Tomas. Detailed modeling of flue-gas desulfurization plant. Computers & Chemical Engineering,2007,31 (11):1419-1431.
[24]S. Sarkar, B. C. Meikap, S. G. Chatterjee. Modeling of removal of sulfur dioxide from flue gases in a horizontal cocurrent gas-liquid scrubber. Computers & Chemical Engineering,2007,131 (1):263-271.
[25]E. Grieco, L. Marmo. A model for the pressure balance of a low density circulating fluidized bed. Chemical Engineering Journal,2008,140 (1): 414-423.
[26]F. Ruhland, R. Kind, S. Weiss. The kinetics of absorption of sulfur dioxide in calcium hydroxide suspensions. Chemical Engineering Science,1991,46 (4): 939-947.
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