
针对电站负荷变动工况下锅炉氮氧化物排放浓度难以有效预测的问题,提出了一种考虑输入变量时延-特征提取的电站锅炉氮氧化合物(NO
x
)排放动态建模方法,该方法将主元分析和高斯回归建模相结合,利用主元分析提取输入变量数据特征信息,将提取信息的当前值和历史序列值作为高斯回归模型的输入;此外,锅炉NO
x
浓度的历史时间序列值作为反馈数据添加到模型的输入中。以某1 000 MW超超临界机组锅炉燃烧系统为对象,结合现场实际运行数据建立锅炉NO
x
排放动态模型。实验结果表明:所建锅炉NO
x
排放动态模型具有较高的预测精度和较强的泛化性能,对锅炉NO
x
排放建模及智能控制研究有一定参考价值。
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