• 论文
主办单位:煤炭科学研究总院有限公司、中国煤炭学会学术期刊工作委员会
基于机器学习的燃煤锅炉燃烧效率在线计算
  • Title

    Online calculation of coal-fired boiler combustion efficiency based on machine learning

  • 作者

    陈波曹歌瀚黄亚继岳峻峰徐文韬王亚欧李雨欣金保昇

  • Author

    CHEN Bo,CAO Gehan,HUANG Yaji,YUE Junfeng,XU Wentao,WANG Ya′ou,LI Yuxin,JIN Baosheng

  • 单位

    江苏方天电力技术有限公司东南大学 东南大学 能源热转换及其过程测控教育部重点实验室

  • Organization
    Jiangsu Frontier Electric Power Technology Co.,Ltd.,;Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education,Southeast University
  • 摘要

    经济发展方向与政策导向促使火电厂燃煤锅炉朝着智能化方向升级,燃煤锅炉的燃烧效率是衡量锅炉运行状况的重要指标。为了满足实时计算锅炉热效率的要求,借助于电厂的日常测量数据计算锅炉效率,计算方法为:① 分析锅炉的燃烧运行特征;② 根据提取的特征采用剔除异常数据、稳态判别、相似性处理的预处理方法,生成更好的训练样本;③ 采用遗传算法改进的神经网络算法建立锅炉排烟温度、飞灰含碳量和煤质灰分之间的计算模型;利用燃煤热值与理论空气量的比例关系计算入炉煤热值,计算值用于锅炉热效率的反平衡计算模型。计算结果表明,神经网络模型的预测值能满足工程计算的要求;计算所得的排烟温度、飞灰含碳量与煤质灰分用于锅炉效率的计算过程,可实现实时动态的锅炉效率计算;计算所得锅炉效率的变化与实际蒸发量变化基本一致。锅炉实际蒸发量下降时,锅炉效率降低;锅炉实际蒸发量保持60%以上额定蒸发量时,锅炉效率易保持在较高水平。

  • Abstract

    The direction of economic development and policy orientation has promoted the upgrading of coal-fired boilers in thermal power plants towards the direction of intelligence. The combustion efficiency of coal-fired boiler is an important indicator to measure the operating status of boiler. In order to meet the requirements of real-time calculation of boiler thermal efficiency,the following methods are used to calculate the boiler efficiency with the help of the daily measurement data of the power plant:Firstly,the corresponding combustion and operation characteristics of the boiler were analyzed; Secondly,according to the extracted features,the preprocessing methods of eliminating outliers,steady state discrimination,and similarity processing were carried out to generate better training samples. Finally,the neural network algorithm improved by genetic algorithm was used to establish the calculation model among the boiler exhaust temperature,fly ash carbon content and coal ash content. The calorific value of the coal into the furnace was calculated by using the proportional relationship between the calorific value of coal and the theoretical air volume,and the calculated value was used in the inverse balance calculation model of the boiler thermal efficiency. The calculation results show that the predicted value of the neural network model can meet the requirements of engineering calculation. The calculated exhaust gas temperature,fly ash carbon content and coal ash content can be used in the calculation of boiler efficiency to realize real-time dynamic boiler efficiency calculation. The change of the calculated boiler efficiency is approximately the same as that of the actual evaporation change. When the actual evaporation capacity of the boiler decreases,the efficiency of the boiler will decrease. When the actual evaporation capacity of the boiler is maintained above 60% of the rated evaporation capacity,the boiler efficiency is easily maintained at a high level.

  • 关键词

    机器学习 神经网络算法 遗传算法 数据分析 锅炉效率

  • KeyWords

    machine learning;neural network algorithm;genetic algorithm;data analysis;boiler efficiency

  • 基金项目(Foundation)
    国家重点研发计划资助项目(2018YFC1901200);江苏方天电力技术有限公司科技项目(KJ201927);江苏省科技成果转化专项基金资助项目(BA2020001)
  • 文章目录

    0 引言

    1 目标锅炉与燃烧系统

    2 数据预处理

    3 锅炉效率计算

    4 遗传算法改进的神经网络模型

    5 结果与分析

    6 结论

  • 引用格式
    陈波,曹歌瀚,黄亚继,等.基于机器学习的燃煤锅炉燃烧效率在线计算[J].洁净煤技术,2021,27(4):174-179.
    CHEN Bo,CAO Gehan,HUANG Yaji,et al.Online calculation of coal-fired boiler combustion efficiency based on machine learning[J].Clean Coal Technology,2021,27(4):174-179.
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