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<p>To realize the effective utilization of biomass resources, the combustion characteristics of straw, sludge, herb residue, lean coal and their mixture under different blending rates were studied. Thermogravimetric analysis experiments were conducted to analyze the combustion performances and the synergistic effects of coal and biomass. Based on the artificial neural network (ANN) model, the thermogravimetric profile of the sample was established. The results show that all samples burn out before 800&#xa0;°C. The blending of biomass can lower the ignition temperature and improve the ignition characteristics of pulverized coal. In the combustion process, there is the interaction between biomass and coal. With increasing the biomass blending ratio, the inhibition impact in the combustion stage of volatile matter is enhanced, while the inhibition impact in the burning stage of fixed carbon is weakened, and finally a synergistic effect promotes the combustion process. ANN45 is considered the optimal model to predict coal and biomass co-combustion, and its RMSE, MAE and <i>R</i><sup>2</sup> are 0.3040, 0.2233 and 0.9999, respectively.</p>

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Analysis and prediction of combustion characteristics of co-combustion of coal and biomass (straw, sludge and herb residue)

  • 期刊论文

  • 发表日期：

    2025年2月10日

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  • Ming Lei,
  • Hui Han,
  • Xi Tian,
  • Lei Zhang,
  • Qian Zhang

摘要

To realize the effective utilization of biomass resources, the combustion characteristics of straw, sludge, herb residue, lean coal and their mixture under different blending rates were studied. Thermogravimetric analysis experiments were conducted to analyze the combustion performances and the synergistic effects of coal and biomass. Based on the artificial neural network (ANN) model, the thermogravimetric profile of the sample was established. The results show that all samples burn out before 800 °C. The blending of biomass can lower the ignition temperature and improve the ignition characteristics of pulverized coal. In the combustion process, there is the interaction between biomass and coal. With increasing the biomass blending ratio, the inhibition impact in the combustion stage of volatile matter is enhanced, while the inhibition impact in the burning stage of fixed carbon is weakened, and finally a synergistic effect promotes the combustion process. ANN45 is considered the optimal model to predict coal and biomass co-combustion, and its RMSE, MAE and R2 are 0.3040, 0.2233 and 0.9999, respectively.