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

作　　者：李科莹 LI Keying(Guizhou Xingyi Electric Power Development Co.,Ltd.,Xingyi,Guizhou 562400,China)

机构地区：[1]贵州兴义电力发展有限公司,贵州兴义562400

出　　处：《自动化应用》2024年第7期97-99,108,共4页Automation Application

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。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 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]