SCR denitration system modeling and operation optimization simulation for thermal power plant

被引：0

作者：

Qin T. ^{[1
]}

Liu J. ^{[1
]}

Yang T. ^{[1
]}

Zhang W. ^{[1
]}

机构：

[1] State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources, North China Electric Power University, Changping District, Beijing

来源：

Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering | 2016年 / 36卷 / 10期

关键词：

Data modeling; Flue gas denitration; Kernel partial least squares (KPLS); Optimal control; Selective catalytic reduction (SCR);

D O I：

10.13334/j.0258-8013.pcsee.2016.10.014

中图分类号：

学科分类号：

摘要：

Selective catalytic reduction (SCR) method is widely used for flue gas denitration of thermal power plants. Spraying ammonia flow can affect the efficiency of flue gas denitration. Excess ammonia injection will result in higher rates of ammonia slip which will cause pollution. Reaction processes of SCR systems are very complex and SCR system has the characteristics of nonlinear and large inertia. Therefore, it is difficult for the traditional PID control methods to achieve precise control of the amount of ammonia injection. Multi-scale kernel partial least squares (MKPLS) modeling method was employed to development SCR system model. The simulation results show that the model has high accuracy and the generalization ability of the model is good. In order to achieve the optimal control of the ammonia injection, model predictive control method is combined with the MKPLS model. Experimental results show that comparing with traditional PID control this method achieves the accurate control of the amount of ammonia and improves the denitration rate as well as avoids excessive ammonia injection. © 2016 Chin. Soc. for Elec. Eng.

引用

页码：2699 / 2703

页数：4

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