华电技术 ›› 2020, Vol. 42 ›› Issue (9): 37-44.

• 系统模拟与优化 • 上一篇    下一篇

基于智慧模型的脱硝控制系统优化

  

  1. 华电国际电力股份有限公司莱城发电厂,济南 271100
  • 出版日期:2020-09-25 发布日期:2020-09-28

Application of intelligent model in denitration control system optimization

  1. Laicheng Power Plant of Huadian International Power Company Limited,Ji'nan 271100,China
  • Online:2020-09-25 Published:2020-09-28

摘要: 针对目前火电厂选择性催化还原(SCR)脱硝系统存在的脱硝系统入口与出口测量延迟、NOx某测点测量值失真、脱硝反应器出口测量值与脱硝环保测量值不一致等问题,以某电厂300 MW机组为例,对脱硝自动控制系统进行智能优化改进,在保证机组脱硝系统满足超低排放要求的同时,防止氨气过量,出现氨逃逸。采用人工智能技术建立SCR脱硝系统模型,利用智慧优化控制系统(TOCS)强大的自学习与自我进化能力不断完善系统模型,实现对系统运行状态的预测和各控制量的精确计算。TOCS投运后大幅改进了脱硝系统的控制品质,在保证NOx排放达标的基础上,显著减少了系统喷氨量,氨逃逸得到有效控制。

Abstract: Current denitration systems of thermal power plants has some problems such as delayed measurement at denitration inlets and outlets, distorted values at some NOx measuring points, and inconsistency between values measured at denitration reactor outlets and denitration environmental protection devices. To deal with these problems, a 300 MW power plant is taken as an example for the intellectualization and optimization of its denitration control system. The optimized denitration system can meet the requirements of ultra-low emission, and prevent ammonia escape led by excessive ammonia. Artificial intelligence technology is used in building the SCR denitration system model which can be continuously improved by powerful self-taught learning and intelligence development of the technical optimization control system(TOCS).Then,the operation state can be predicted and the control quantity can be accurately calculated.After the running of TOCS, quality control of denitration systems can be largely improved with reduced ammonia spraying volume and mitigated ammonia escape on the premise of NOx emission conforming to standards.