基于PSO优化的模糊控制器在选择性催化还原脱硝技术中的应用
Application of PSO Optimisation Based Fuzzy Controller in Selective Catalytic Reduction Denitrification Technology
李科莹1
作者信息
- 1. 贵州兴义电力发展有限公司,贵州兴义 562400
- 折叠
摘要
工业领域常常会产生大量的NOx污染物,而选择性催化还原脱硝是一种常用于减少污染物排放的技术.该技术在应用过程中面临参数选择困难、稳定性差的问题,因此,需通过粒子群优化的模糊控制器来提高其性能.结果显示,仿真模型出口NOx浓度波动减少30%,氨气流量稳定,稳态与变负荷下控制效果更好,设定值与实际值偏差减少15%.该方法能提高脱硝效率,并能保持系统的稳定性.
Abstract
The industrial sector often generates a large amount of NOx pollutants,and selective catalytic reduction denitrification is a commonly used technology to reduce pollutant emissions.This technology faces difficulties in parameter selection and poor stability during application,therefore,it is necessary to improve its performance through a fuzzy controller optimized by particle swarm optimization.The results show that the fluctuation of NOx concentration at the outlet of the simulation model is reduced by 30%,the ammonia flow rate is stable,and the control effect is better under steady-state and variable load conditions.The deviation between the set value and the actual value is reduced by 15%.This method can improve denitrification efficiency and maintain system stability.
关键词
选择性催化/还原脱硝/粒子群/模糊控制器Key words
selective catalysis/reductive denitrification/particle swarm/fuzzy controller引用本文复制引用
出版年
2024
NETL
NSTL
万方数据