徐爱民, 周建忠, 宋玉彩, 邓博文, 胡卿, 张海丹, 陈俊, 梁钰昆. 国内动力煤热值及可磨性指数测算模型[J]. 选煤技术, 2021, 49(5): 24-27. DOI: 10.16447/j.cnki.cpt.2021.05.005
    引用本文: 徐爱民, 周建忠, 宋玉彩, 邓博文, 胡卿, 张海丹, 陈俊, 梁钰昆. 国内动力煤热值及可磨性指数测算模型[J]. 选煤技术, 2021, 49(5): 24-27. DOI: 10.16447/j.cnki.cpt.2021.05.005
    XU Aimin, ZHOU Jianzhong, SONG Yucai, DENG Bowen, HU Qing, ZHANG Haidan, CHEN Jun, LIANG Yukun. Domestic power coal calorific value and grindability index prediction model[J]. Coal Preparation Technology, 2021, 49(5): 24-27. DOI: 10.16447/j.cnki.cpt.2021.05.005
    Citation: XU Aimin, ZHOU Jianzhong, SONG Yucai, DENG Bowen, HU Qing, ZHANG Haidan, CHEN Jun, LIANG Yukun. Domestic power coal calorific value and grindability index prediction model[J]. Coal Preparation Technology, 2021, 49(5): 24-27. DOI: 10.16447/j.cnki.cpt.2021.05.005

    国内动力煤热值及可磨性指数测算模型

    Domestic power coal calorific value and grindability index prediction model

    • 摘要: 工业分析、元素分析、热值和可磨性指数是电厂动力煤的基本参考指标,热值是燃煤电厂热量输入的关键,煤种的可磨性是衡量制粉系统能耗的重要指标,热值和可磨性指数对燃煤电厂选择合适煤种至关重要。为了研究工业分析、元素分析与热值、可磨性指数(HGI)之间的关联性,选取32种国产动力煤粉为检测样品进行了试验分析。结果表明:门捷列夫低位热值经验公式计算值普遍比实测值高,通过修正门捷列夫经验公式,可减小计算值和测量值之间的标准方差;同时得到了基于工业分析的HGI经验公式,但HGI和工业分析参数之间的相关性较弱,因此HGI的经验预测模型还需要进一步完善。

       

      Abstract: The parameters obtained through proximate analysis, elementary analysis and the analysis of calorific value and grindability index are the basic indicators of the characteristics and property of power coal while the calorific value is a parameter of crucial importance to the heat input of coal-fired power plant, and the grindability of the coal is an important parameter to measure the energy consumption of coal pulverizing system. Hence, calorific value and grindability index are of vital importance for power to select suitable coal for use as fuel. A study is made in the paper of the correlation between the results of both proximate and elementary analysis, calorific value and grindability index (HGI) with 32 kinds of domestic pulverized power coal samples. Test result indicates that the net calorific value calculated using Mendeleev′s empirical formula is generally higher than the actually measured value and the standard variance between the calculated and measured values can be reduced by modifying Mendeleev′s empirical formula. Additionally, the empirical formula of HGI is derived based on proximate analysis, but the HGI and the parameters obtained through proximate analysis are found to be easily correlated. So, the HGI prediction model needs to be further improved.

       

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