摘要
借助现场燃烧调整试验数据,采用最小二乘支持向量机方法建立了NOx排放和燃烧效率的预测模型,并与遗传算法相结合,分别对降低NOx排放和提高锅炉效率的各参数进行了优化,找到了在燃用不同煤种下较低NOx排放和较高燃烧效率的运行参数组合.研究结果证明:运用此方法可以寻找出锅炉在燃用不同煤种时最佳的高效、低污染运行方案.
The estimation model has been established by means of the least squares support vector machine based on combustion adjustment testing conduced on site and incorporated with genetic algorithms. It is used to optimize several parameters related to reduced NOx emission and to enhance boiler efficiency and eventualloy the optimized operation parameter groups can be found out when burning different kind of coals. It is also proven by the research result that the boiler best operation approach of ＂low emission and high efficiency＂ can be determined in case of burning different coals.
出处
《动力工程》
EI
CSCD
北大核心
2008年第3期361-366,共6页
Power Engineering
基金
上海市科委重大攻关项目子课题资助项目(05dz12027)
关键词
能源与动力工程
锅炉
氮氧化物
燃烧优化
最小二乘支持向量机
遗传算法
energy and power engineering
boiler
NOx
combustion optimization
least squares support vector machine
genetic algorithms
