采用电厂日常煤质检测数据预测元素分析成分  

Prediction of Element Analysis of Coal Using the Routine Test Data of Industrial Analysis in Utility Boiler

作　　者：刘福国 刘科[1,2] 吕瑞敏 LIU Fuguo;LIU Ke;LYU Ruimin(Stat Grid Shandong Electric Power Research Institute,Jinan 250002,China;Shandong Electric Power Research Institute,Jinan 250003,China;Shandong Analysic and Test Center,Jinan 250001,China)

机构地区：[1]国网山东省电力公司电力科学研究院,山东济南250003 [2]山东电力研究院,山东济南250003 [3]山东省分析测试中心,山东济南250001

出　　处：《山东电力技术》2021年第2期51-57,共7页Shandong Electric Power

基　　金：山东省重大科技创新工程项目(2019JZZY010420);山东电力研究院科技项目“煤场掺配优化提高机组运行安全性研究”(ZY-2021-17)。

摘　　要：元素分析是煤能量转换过程效率分析的基本数据,常用于确定电厂锅炉燃烧空气量、排烟烟气量以及烟气成分等参数,可帮助运行人员选择合理的炉膛送风量,降低排烟热损失和风机电耗。元素成分的检测较为复杂,而工业分析成分容易进行。给出一种根据电厂日常检测的工业分析数据确定煤的元素成分含量的方法,该方法建立了工业分析成分和元素分析成分之间的关联式,以及发热量和元素成分之间的关联式,通过求解这些关联式和元素成分约束方程组成的方程组,得到煤元素成分含量的多变量线性模型。研究表明,在95%的置信概率下,C_(daf)、H_(daf)、O_(daf)、N_(daf)等元素质量分数预测不确定度为4.61、1.16、3.74和0.53。Element analysis is one of the most important properties of coal for analysis of energy conversion process,and frequently used to determine stoichiometric air requirement and flow rate of flue gas,which is highly valuable for maintaining an appropriate proportion of air and coal into the combustion chamber,reducing heat loss as result of excess air supply,as well as minimizing power consumed to convey air and flue gas throughout the furnace.The experimental determination of elemental analysis are complicated and require special instrumentation,while the industrial analysis needs only common equipment and is much easier to carry out.A novel method was developed to formulate the multivariate linear model to predict element analysis of coal by solving a set of simulta⁃neous equations composed of correlations between industrial analysis、calorific power and element analysis of coal.The results show that under 95%confidence probability,the uncertainty of C_(daf)、H_(daf)、O_(daf)、N_(daf) are 4.61,1.16,3.74 and 0.53,respectively.

关 键 词：煤 元素分析 工业分析 元素成分含量预测 

分 类 号：TM621.2[电气工程—电力系统及自动化]