洁净煤技术

2020, v.26;No.125(01) 71-76

[打印本页] [关闭]
本期目录(Current Issue) | 过刊浏览(Past Issue) | 高级检索(Advanced Search)

煤粉富氧燃烧着火温度预测的优化随机森林(GA-RF)模型
Prediction of ignition temperature of pulverized coal under oxy-fuel combustion condition based on optimized random forest(GA-RF) model

彭潮;兰彦冰;邹春;蔡磊;
PENG Chao;LAN Yanbing;ZOU Chun;CAI Lei;State Key Laboratory of Coal Combustion,Huazhong University of Science and Technology;School of Environmental Science and Engineering,Huazhong University of Science and Technology;

摘要(Abstract):

二氧化碳排放是造成温室效应的主要原因之一,富氧燃烧作为一种有效的碳减排与封存技术具有广泛的研究前景。在燃煤电厂中煤粉富氧燃烧的着火温度是燃烧器设计和运行安全的重要指标,并且与煤粉组成成分、煤粉粒径以及燃烧氛围都有复杂的相关性。因此,对煤粉富氧燃烧着火温度的预测模型研究意义重大。采用滴管炉分别测量了5种煤粉在O_2体积分数为30%、35%、40%、50%、60%、70%、80%、90%、100%富氧条件下的着火温度,分析了氧气体积分数和煤粉的组成成分与着火温度之间的关系。研究发现,随着氧气体积分数分数的增加,5种煤样的着火温度均显著下降,且挥发分越高的煤,下降幅度越大。将45组试验着火温度数据与其他研究者采用同样方法测得的69组着火温度数据组成机器学习样品库,以煤粉的元素分析、工业分析、煤粉粒径及氧气体积分数为输入条件,以着火温度T为目标输出,构建了遗传算法优化的随机森林模型(GA-RF模型),准确预报了煤粉富氧燃烧的着火温度,其预报精度为:R~2>0.99,RMSE<16,MAE<8。通过模型参数重要性分析发现,氢组分超过5%后,着火温度出现阶跃式上升,现有煤粉着火数据也证实了该现象。
Carbon dioxide emission is one of the main reasons for the greenhouse effect. Oxy-fuel combustion has an extensive research prospect as an effective carbon emission reduction and storage technology.The ignition temperature of pulverized coal in oxy-fuel combustion in coal-fired power plants is an important indicator of burner design and operational safety,which has complex correlations with the composition of coal,coal particle size,and the atmosphere of combustion. Therefore,the research of the ignition temperature prediction model of pulverized coal oxy-fuel combustion is very meaningful. In this study,the ignition temperatures of five coal samples were measured in dropper furnace under 30%,35%,40%,50%,60%,70%,80%,90% and 100% volume fraction of O_2 in CO_2 atmosphere.The relationship between coal ignition temperature and the oxygen concentration and the composition of pulverized coal was analyzed.The research finds that the coal ignition temperature decreases significantly with the increase of oxygen concentration,and the degree of decrease is higher when the coal sample contains more volatile.A machine learning sample base with 45 sets of coal ignition temperature in the experiment and 69 sets of ignition temperature collected from recent year' s research with the same measurement was established.The ultimate analysis and proximate analysis of the pulverized coal,the coal particle size and the oxygen volume fraction were selected as the input features,and the ignition temperature was the target output,a random forest model optimized by genetic algorithm( GA-RF model)was constructed and the ignition temperature of pulverized coal in oxy-fuel combustion was accurately predicted,with the accuracy of R~2>0.99,RMSE<16,MAE<8.The feature importance of ignition temperature shows that the ignition temperature increases immediately when the H content is over 5%,which is proved by the existing ignition data of pulverized coal.

关键词(KeyWords): 煤粉;富氧燃烧;着火温度;随机森林;遗传算法
pulverized coal;oxy-fuel combustion;ignition temperature;random forest;genetic algorithm

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金面上资助项目(51776081)

作者(Author): 彭潮;兰彦冰;邹春;蔡磊;
PENG Chao;LAN Yanbing;ZOU Chun;CAI Lei;State Key Laboratory of Coal Combustion,Huazhong University of Science and Technology;School of Environmental Science and Engineering,Huazhong University of Science and Technology;

Email:

参考文献(References):

文章评论(Comment):

序号(No.) 时间(Time) 反馈人(User) 邮箱(Email) 标题(Title) 内容(Content)
反馈人(User) 邮箱地址(Email)
反馈标题(Title)
反馈内容(Content)
扩展功能
本文信息
服务与反馈
本文关键词相关文章
本文作者相关文章
中国知网
分享