甘加耀, 钟文琪, 周冠文, 陈曦, 石建良, 刘彦新. 复杂煤种锅炉水冷壁结渣特性的数值模拟及防结渣配煤优化[J]. 中国电机工程学报, 2021, 41(22): 7681-7691. DOI: 10.13334/j.0258-8013.pcsee.202052
引用本文: 甘加耀, 钟文琪, 周冠文, 陈曦, 石建良, 刘彦新. 复杂煤种锅炉水冷壁结渣特性的数值模拟及防结渣配煤优化[J]. 中国电机工程学报, 2021, 41(22): 7681-7691. DOI: 10.13334/j.0258-8013.pcsee.202052
GAN Jiayao, ZHONG Wenqi, ZHOU Guanwen, CHEN Xi, SHI Jianliang, LIU Yanxin. Numerical Simulation Study on Slagging Characteristics and Coal Blending Optimization of Anti-slagging of Water-wall of Coal-fired Boiler Under Complex Types of Coal[J]. Proceedings of the CSEE, 2021, 41(22): 7681-7691. DOI: 10.13334/j.0258-8013.pcsee.202052
Citation: GAN Jiayao, ZHONG Wenqi, ZHOU Guanwen, CHEN Xi, SHI Jianliang, LIU Yanxin. Numerical Simulation Study on Slagging Characteristics and Coal Blending Optimization of Anti-slagging of Water-wall of Coal-fired Boiler Under Complex Types of Coal[J]. Proceedings of the CSEE, 2021, 41(22): 7681-7691. DOI: 10.13334/j.0258-8013.pcsee.202052

复杂煤种锅炉水冷壁结渣特性的数值模拟及防结渣配煤优化

Numerical Simulation Study on Slagging Characteristics and Coal Blending Optimization of Anti-slagging of Water-wall of Coal-fired Boiler Under Complex Types of Coal

  • 摘要: 为掌握复杂煤种对水冷壁结渣特性的影响规律并开展防结渣配煤优化,采用组分输运模型对一台330MW四角切圆锅炉的燃烧过程展开三维数值模拟,研究了I(高灰分Aar > 35%、低热值Qar, net < 15.5MJ/kg)、II(中等灰分25% < Aar < 35%、中等热值15.5MJ/kg < Qar, net < 19.7MJ/kg)、III(低灰分Aar < 25%、高热值Qar, net > 19.7MJ/kg)这3类煤在不同配煤方式下对水冷壁结渣的影响,并进行结渣评估和防结渣配煤优化。结果表明:不同配煤方式下温度引起水冷壁结渣的区域和程度大致相同,而由于CO浓度引起水冷壁结渣的差异较大;相较于煤种炉外掺混,煤种炉内掺混时CO浓度变化幅度更大;为减轻水冷壁结渣,煤种炉内掺混时,建议燃烧器底下两层采用Ⅱ类煤、燃烧器3、4层采用Ⅰ类煤、燃烧器最上层采用Ⅲ类煤;煤种炉外掺混时,建议燃烧器底下两层采用Ⅰ、Ⅱ类煤、燃烧器3、4层采用Ⅱ、Ⅲ类煤、燃烧器最上层采用Ⅰ、Ⅲ类煤,且各层燃烧器各煤种的最佳掺混比例为1:1。

     

    Abstract: To grasp the influence of complex coal on the slagging of the water-wall and carry out anti-slagging of the coal blending optimization, the species transport model was used to carry out a three-dimensional numerical simulation of the combustion process of a 330MW tangential firing boiler, studying the effects of the three types of coal on the slagging of the water-wall under different blending methods——I(high ash content for Aar is higher than 35%, low calorific value for Qar, net is lower than 15.5MJ/kg), Ⅱ (medium ash content for Aar is between 25% and 35%, medium calorific value for Qar, net is between 15.5MJ/kg and 19.7MJ/kg), and III(low ash content for Aar is lower than 25%, high calorific value for Qar, net is higher than 19.7MJ/kg), and performed slagging evaluation and coal blending optimization. The study found that the area and degree of slagging on the water-wall caused by temperature under different coal blending methods were roughly the same, but the difference of slagging on the water-wall due to CO concentration was greater. Compared with the coals blending outside the boiler furnace, the CO concentration changed more when the coals were blended in the boiler furnace. To reduce the slagging, when coals are blended in the furnace, it is recommended that the bottom two layers of the burner adopt coal of type II, the 3rd and 4th layers of the burner adopt coal of type I, and the uppermost layer of the burner adopts coal of type III. When coals are blended outside the furnace, it is recommended that the bottom two layers of the burner adopt coal of types I and II, the 3rd and 4th layers adopt coal of types II and Ⅲ, and the uppermost layer adopts coal of types I and III, the best blending ratio of each coal type in each layer of burner is 1:1.

     

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