基于智能控制的典型样本参数优化  

Boiler Combustion Optimization Based on Intelligent Control

作　　者：孙宇航 田亮[1] SUN Yuhang;TIAN Liang(School of Control and Computer Engineering,North China Electric Power University,Baoding 071003,China)

机构地区：[1]华北电力大学控制与计算机工程学院,河北保定071003

出　　处：《电力科学与工程》2022年第3期8-16,共9页Electric Power Science and Engineering

基　　金：国家重点研发计划(2017YFB0902100)。

摘　　要：为提高锅炉效率并降低NOx排放,针对燃烧优化典型样本库,提出一种基于智能控制的参数优化方法。首先,利用模糊控制对辅助风、燃尽风门挡板开度偏置值进行优化,利用系数分配函数实现风门挡板偏置值的分层配置;然后,使用k-近邻模型寻找相似工况,采用相似度阈值函数判断当前工况与典型样本库工况的相似程度,在与典型样本库参数的优化效果对比后择优对典型样本库数据进行更新;最后,对某发电厂机组二次风进行优化。优化后,选择性催化还原装置入口NOx浓度平均下降3.18%,锅炉效率提高0.07%。结果表明,采用模糊控制可以优化二次风挡板开度参数,所提出的智能控制方法能够优化典型样本库数据。In order to improve boiler efficiency and reduce NOx emissions,a parameter optimization method based on intelligent control is proposed for the typical sample library of combustion optimization.First,the fuzzy control is used to optimize the opening offset of the auxiliary air and over-fire air damper,and the coefficient distribution function is used to realize the layered configuration of the damper offset.Then the k-nearest neighbor model is used to find similar operating conditions,and the similarity threshold function is used to judge the similarity between the current operating conditions and the typical sample library operating conditions,and then selects the best to update the typical sample library data after comparing with the optimization effect of the typical sample library parameters.Finally,after optimizing the secondary air of units in a power plant,it is shown that the NOx concentration at the inlet of the selective catalytic reduction(SCR)device drops by 3.18%on average after the optimization,and the boiler efficiency is increased by 0.07%.Using fuzzy control can optimize the opening parameters of the secondary air damper.The proposed intelligent control method can optimize typical sample library data.

关 键 词：燃煤锅炉 燃烧优化 典型样本 NOX排放 智能控制 

分 类 号：TM3[电气工程—电机]