摘要
针对电厂循环流化床锅炉NOx排放问题进行了研究,并对人工蜂群算法进行了改进,结合最小二乘支持向量机建立了锅炉燃烧NOx排放模型,对锅炉可调参量进行了优化,降低了NOx排放浓度。将改进的人工蜂群算法与基本的人工蜂群算法和粒子群算法进行比较,说明基于改进人工蜂群算法所建立的模型能够很好的预测NOx的排放浓度,具有很强的辨识能力和泛化能力,同时也表明了改进人工蜂群算法计算速度快的优点及优化数据上的优势,通过仿真试验,优化后NOx排放浓度明显降低,体现了其工程实用价值。
Studied were the problems relating to the NOxemissions of circulating fluidized bed boilers in power plants and improved was the artificial swarm algorithm. In combination with the least square supporting vector machine,the authors established a model for the NOxemissions of boilers and optimized the adjustable parameters of the boiler and reduced the NOxemissions concentration. A comparison of the improved artificial swarm algorithm with the basic artificial swarm algorithm and the particle colony algorithm indicates that the model based on the improved artificial swarm algorithm can predict very well the NOxemissions concentration and boasts a very strong identification and generalization ability,and at the same time,it also indicates that the improved artificial swarm algorithm is quick in calculation and has an edge in optimizing data. Through a simulation test,the optimized NOxemissions concentration can obviously decrease,displaying its practical value in engineering applications.
出处
《热能动力工程》
CAS
CSCD
北大核心
2014年第4期427-433,462,共7页
Journal of Engineering for Thermal Energy and Power
基金
国家自然科学基金资助项目(60774028)
河北省自然科学基金资助项目(F2010001318)
关键词
锅炉燃烧优化
最小二乘支持向量机
NOx排放浓度
人工蜂群算法
boiler combustion optimization,least square supporting vector machine,NOxemissions concentration,artificial swarm algorithm
