[1]张珑慧,林德海,王 颖,等.机器学习在火电厂NOx减排中的应用综述[J].热力发电,2023,52(01):7-17.[doi:10.19666/j.rlfd.202206132]
　ZHANG Longhui,LIN Dehai,WANG Ying,et al.Review of applications of machine learning in nitrogen oxides reduction in thermal power plants[J].Thermal Power Generation,2023,52(01):7-17.[doi:10.19666/j.rlfd.202206132]
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机器学习在火电厂NOx减排中的应用综述

《热力发电》[ISSN:1002-3364/CN:61-1111/TM] 卷: 52 期数: 2023年01期 页码: 7-17 栏目: 技术经济综述 出版日期: 2023-01-08
Title:
Review of applications of machine learning in nitrogen oxides reduction in thermal power plants
作者:
张珑慧1; 林德海1; 王 颖2; 季广辉3; 马少丹1; 曹子雄1;  刘 伟1; 刘子林1; 马子然1; 王宝冬1
1.北京低碳清洁能源研究院，北京 102209；2.北方工程设计研究院有限公司，河北 石家庄 050000；3.河北国华定州发电有限责任公司，河北 定州 073000
Author(s):
ZHANG Longhui1;  LIN Dehai1;  WANG Ying2;  JI Guanghui3;  MA Shaodan1;  CAO Zixiong1; LIU Wei1;  LIU Zilin1;  MA Ziran1;  WANG Baodong1
1. National Institute of Clean and Low Carbon Energy, Beijing 102209, China; 2. North Engineering Design and Research Institute Co., Ltd., Shijiazhuang 050000, China;3. Hebei Guohua Dingzhou Power Generation Co., Ltd., Dingzhou 073000, China
关键词:
NOx排放; SCR; 模型预测控制; 大数据; 机器学习
DOI:
10.19666/j.rlfd.202206132
摘要:
随着火电厂超低排放改造的完成，产生了成本增加、喷氨超标等问题。通过机器学习对电厂运行数据建模和优化成为解决这一问题的重要手段。综述了NOx减排中常用的机器学习算法及其应用场景。在算法方面，归纳了数据预处理、算法模型和模型参数优化3个过程的研究现状，给出了各个过程多种机器学习算法的应用情况及适用性，提出了变工况数据预处理方法、多目标优化中目标函数的构造方法等未来研究方向。在应用层面，总结了机器学习在炉内低氮燃烧、选择性催化还原（SCR）烟气脱硝系统运行优化、全系统综合节能降耗等过程的实施方法及其运行效果，展望了长周期动态建模控制及多电厂联合建模等未来应用场景。

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（责任编辑 杜亚勤）

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备注/Memo

张珑慧（1989），女，博士，工程师，主要研究方向为大气污染物治理及智慧电厂，longhui.zhang@chnenergy.com.cn。

更新日期/Last Update: 2023-01-15