摘要
利用人工神经网络对锅炉飞灰含碳量进行建模，并采用混合遗传算法与复合形法进行运行工况寻优，获得当前最佳的锅炉燃烧调整方式，这种方法同时解决了锅炉变工况下运行参数基准值的问题。应用该模型对某台300MW四角切圆燃煤电站锅炉的飞灰含碳量进行优化控制研究，其结果可指导运行人员进行参数优化调整，降低锅炉飞灰含碳量，提高燃烧经济性。
By setting up a neural network model of carbon content in fly ash of boilers, and determining the optimized mode of operation with the help of hybrid genetic algorithm as well as by the compound formation method, the currently best way of adjusting boiler combustion has been obtained, which simultaneously provides a means for finding the basic operational parameters of a boiler under changing modes of operation, With this model the optimization control problem of carbon content in the fly ash of a certain 300MW pulverized coal corner fired utility boiler is being treated, the results of which may serve operators as a guide for optimizing the parameters, reducing the carbon content in the fly ash and raising combustion efficiency. Figs 3, tables 4 and refs 7,
出处
《动力工程》
EI
CAS
CSCD
北大核心
2005年第3期391-391,共1页
Power Engineering
关键词
电站锅炉
人工神经网络
飞灰
含碳量
优化控制
automatic control technique
fly ash＇s carbon content
neural network
genetic algorithm
compound formation method
combustion optimization
