摘要
燃煤锅炉NOx排放是造成环境污染的重要因素,影响NOx排放的因素众多而且复杂。首先建立了锅炉NOx排放支持向量机模型,并利用实炉热态数据对模型进行了校验。接着应用一种改进的粒子群优化算法,对锅炉运行参数进行了优化,并与一般线性粒子群优化算法进行了对比。结果表明,NOx排放量均有明显的降低,但改进的优化算法收敛性更好,为优化锅炉燃烧提供了更好的方式。
NOx emission of coal-fired boiler is a main factor that has great impacts on the environment.It was affected by many factors and they are complicated.Firstly,a support vector machine（SVM） model of NOx emission was developed and verified by the data on-spot.Then,operating parameters were optimized by an improved linear particles swarm optimization（ILPSO）,and compared with the linear particles swarm optimization（LPSO）.The results show that NOx emissions are significantly lower,and ILPSO algorithm has better convergence.It has improved a better way to optimize boiler combustion.
出处
《系统仿真学报》
CAS
CSCD
北大核心
2011年第12期2812-2815,共4页
Journal of System Simulation
基金
国家973计划资助项目(2009CB219803-03)
长沙理工大学"可再生能源电力技术"湖南省重点实验室(2009)
关键词
锅炉
燃烧
NOX排放
支持向量机
改进粒子群优化
boiler
combustion
NOx emission
support vector machine（SVM）
Improved Linear Particles Swarm Optimization（ILPSO）
