摘要
利用人工神经网络(ANN)进行锅炉飞灰含碳量建模,并分析二次风配风方式对飞灰含碳量的敏感性影响,同时采用混合遗传算法HGA与复合形法对运行工况寻优,获得各种工况下二次风开度的优化调整方式.应用某台300MW机组的现场试验数据进行仿真计算,结果表明该方法可以指导运行人员进行二次风开度的优化调整,降低飞灰含碳量,同时也解决了锅炉变工况下运行参数基准值的确定问题.
The content of the unburned carbon in fly ash from utility boiler is modeled by ANN （ Artificial Neural Network）, and a sensitivity analysis of the effect of secondary air distribution mode on the unburned carbon is carried out. Meanwhile, the hybrid genetic algorithm （HGA） and the compound form method are employed to search for the optimum solution to the neural network model, thus obtaining optimized distribution modes of secondary air adapting to various operation conditions. By the simulation of the in-site experimental results of a 300MW unit, it is finally concluded that the proposed distribution mode of secondary air is feasible and helps to reduce the content of unburned carbon in fly ash. Moreover, the operation standard values of boiler parameters in different operation conditions can be determined by the proposed method.
出处
《华南理工大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2006年第4期96-100,共5页
Journal of South China University of Technology(Natural Science Edition)
关键词
飞灰含碳量
二次风配风
神经网络
混合遗传算法
敏感性分析
unburned carbon content
secondary air distribution
neural network
hybrid genetic algorithm
sensitivity analysis
