摘要
电站锅炉面临降低运行成本与降低污染物排放的双重要求。依据采集到的燃烧数据,采用神经网络训练得到了锅炉燃烧模型,用于预测锅炉在不同燃烧参数的NOx排放和燃烧效率。并采用多目标优化算法,通过调整锅炉运行参数,在锅炉高效燃烧与NOx低排放之间找到合理的平衡点。
There are double requirements of both reducing operating cost and decreasing contaminant emission for power station boilers. A boiler combustion model has been obtained with the training of neural network based on combustion data collected, which can be used to forecast the NOx emission and combustion efficiency of the boiler with different combustion parameters. A reasonable balance point is found between high efficiency and low NOx emission of the boiler based on multi-objective optimization and operation data adjustment.
出处
《发电设备》
2012年第2期97-99,118,共4页
Power Equipment
关键词
锅炉
燃烧
神经网络
多目标优化
NOX排放
热效率
boiler
combustion
neural network
multi-objective optimization
NOx emission
thermal efficiency
