基于多变量广义预测控制算法的脱硝优化研究及应用

doi:10.11930/j.issn.1004-9649.201901009

中国电力 ›› 2019, Vol. 52 ›› Issue (10): 178-184.DOI: 10.11930/j.issn.1004-9649.201901009

• 节能与环保 • 上一篇

基于多变量广义预测控制算法的脱硝优化研究及应用

张晓东¹, 王鹏飞², 刘乐²

1. 中国国电科技环保集团公司, 北京 100761;
2. 北京国电智深控制技术有限公司, 北京 100085

收稿日期:2019-01-13 修回日期:2019-04-30 出版日期:2019-10-05 发布日期:2019-10-12
作者简介:张晓东(1975-),男,硕士,高级工程师,从事电气控制与信息化研究,E-mail:12065306@chnenergy.com.cn;王鹏飞(1991-),男,硕士,工程师,从事电站自动控制与运行优化研究,E-mail:12053875@chnenergy.com.cn;刘乐(1981-),男,硕士,工程师,从事电气控制与信息化研究,E-mail:12051609@chnenergy.com.cn

Research and Application of Denitrification Optimal Control Based on Multi-Variable Generalized Predictive Control Algorithms

ZHANG Xiaodong¹, WANG Pengfei², LIU Le²

1. Guodian Technology & Environment Group Co., Ltd., Beijing 100761, China;
2. Beijing Guodian Zhishen Control Technology Co., Ltd., Beijing 100085, China

Received:2019-01-13 Revised:2019-04-30 Online:2019-10-05 Published:2019-10-12

摘要/Abstract

摘要： 大型火力发电机组脱硝系统被控对象具有大迟延、大惯性、受干扰因素多以及不同负荷下的被控对象模型变化大等特性，传统的PID控制不能满足控制要求。为解决这一问题，利用递推最小二乘法（recursive least square，RLS）建立了脱硝系统多变量模型，并基于多变量广义预测控制构建了脱硝系统优化控制策略，同时将该策略应用于某电厂330 MW亚临界机组。实践结果表明：无论是稳态工况还是复杂的变负荷工况，脱硝优化控制策略都能够很好地控制脱硝系统出口NO_x浓度，大大降低了NO_x浓度的波动，减少了尿素使用量，实现了脱硝系统稳定经济运行。

关键词: 火力发电机组, 脱硝系统, 优化控制, 多变量广义预测控制, 出口NO_x

Abstract: For the denitrification control system of large thermal power unit, because of the characteristics of its controlled object, such as the large time delay and inertia, the impacts from multiple interference factors and model variations under different loads, traditional PID control strategy cannot meet the requirements. Regarding this problem, a multi-variable model of denitrification system is constructed by recursive least square method, and then an optimal control strategy for denitrification system is established based on multi-variable generalized predictive control. Meanwhile, this strategy has been applied in 330 MW subcritical unit of a power plant. From the practical results it is shown that the proposed denitration optimization control strategy based on multi-variable generalized predictive control has effectively controlled NO_x concentration at the denitration outlet and suppressed the fluctuation of NO_x concentration, whether the system is operated under steady state or complex variable load conditions. The usage of urea has also been reduced such that the stable and economic operation of the denitration system is achieved.

Key words: thermal power generating unit, denitration system, optimize control, multi-variable generalized predictive control, NO_x at outlet

中图分类号:

张晓东, 王鹏飞, 刘乐. 基于多变量广义预测控制算法的脱硝优化研究及应用[J]. 中国电力, 2019, 52(10): 178-184.

ZHANG Xiaodong, WANG Pengfei, LIU Le. Research and Application of Denitrification Optimal Control Based on Multi-Variable Generalized Predictive Control Algorithms[J]. Electric Power, 2019, 52(10): 178-184.

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https://www.electricpower.com.cn/CN/Y2019/V52/I10/178

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基于多变量广义预测控制算法的脱硝优化研究及应用

Research and Application of Denitrification Optimal Control Based on Multi-Variable Generalized Predictive Control Algorithms

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基于多变量广义预测控制算法的脱硝优化研究及应用

Research and Application of Denitrification Optimal Control Based on Multi-Variable Generalized Predictive Control Algorithms

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