基于功煤系数的锅炉入炉煤量实时预测模型
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  • 英文篇名:Real-time prediction model of feed coal quantity for boilers based on power to coal coefficient
  • 作者:谷俊杰 ; 张岩 ; 白智中 ; 于文圣
  • 英文作者:GU Junjie;ZHANG Yan;BAI Zhizhong;YU Wensheng;School of Energy Power and Mechanical Engineering,North China Electric Power University;
  • 关键词:锅炉 ; 入炉煤量 ; 实时预测模型 ; 功煤系数 ; 前馈校正 ; 中调指令 ; 组合预测 ; 方差倒数
  • 英文关键词:boiler;;feed coal quantity;;real-time prediction model;;coefficient of power to coal;;feedforward correction;;load instruction;;combined prediction;;variance reciprocal
  • 中文刊名:RLFD
  • 英文刊名:Thermal Power Generation
  • 机构:华北电力大学能源动力与机械工程学院;
  • 出版日期:2016-07-20 14:05
  • 出版单位:热力发电
  • 年:2016
  • 期:v.45;No.356
  • 基金:河北省教育厅科学研究指导性项目(z2007414)
  • 语种:中文;
  • 页:RLFD201607011
  • 页数:6
  • CN:07
  • ISSN:61-1111/TM
  • 分类号:67-72
摘要
锅炉入炉煤的投入量均按照电厂设计煤种进行计算,而电厂燃煤煤种较杂、煤热值波动较大,使得控制锅炉入炉煤量的准确性成为难题。对此,本文采用功煤系数法,依据组合预测模型与方差倒数理论建立了入炉煤量的预测模型,求取待预测时刻前1h功煤系数对当前时刻(待预测时刻)功煤系数的最优权重,实现了对当前时刻功煤系数以及入炉煤煤量的预测,并利用该预测模型对某660MW机组锅炉入炉煤量进行预测。结果表明,用实时入炉煤量的预测值作为实际给煤量,其平均准确度可达到97%以上,表明本文提出的基于功煤系数的入炉煤量预测模型具有较好的应用价值。
        The feed coal quantity of boiler is calculated according to the design coal.However,due to the complexity of feed coal type and the large fluctuations of coal calorific value in power plants,accurately controlling the amount of coal into the furnace has become a difficult problem.Thus,this paper designed the self-adaptive coal quality feedforward correction,and established a prediction model for feed coal quantity,by using the coefficient of power to coal as a starting point,on the basis of the combined prediction model and variance reciprocal method.The optimal weight coefficient of the power to coal coefficient in the last one hour to the current power to coal coefficient was calculated,so the coefficient of power to coal and the amount of feed coal into the furnace can be predicted.Moreover,taking No.4boiler of the 660 MW unit in Guohua Cangdong Power Plant as the example,the feed coal quantity was predicted using the above model.The results show that,using the real-time predicted value as the actual feed coal amount,the average accuracy can reach up to 97%,indicating the proposed prediction model has a good prospect.
引文
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