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Study of optimal pulverized coal concentration in a four-wall tangentially fired furnace

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  • Tan, Houzhang
  • Niu, Yanqing
  • Wang, Xuebin
  • Xu, Tongmo
  • Hui, Shien

Abstract

The effect of fuel lean/rich conditions (1:1, 1:2, 1:3, 1:4, 1:5 and 1:6) on the furnace core temperatures, carbon in fly ash and slag and NOx emissions was investigated in a 1Â MW four-wall tangentially horizontal bias fired furnace for Yibin anthracite and Shenmu bituminous, respectively. Results shown that furnace core temperatures increased at first and then decreased along the height of the furnace when anthracite burned. The furnace core temperature at the height of primary air nozzles was the highest when the bituminous lean/rich varied from 1:1 to 1:3, and its trend was similar to the anthracite when the bituminous lean/rich was changed from 1:4 to 1:6. The ignition of anthracite required a heating stage, while bituminous could timely ignite due to high volatile. However, when the bituminous lean/rich was too low resulting in the relative lack of oxygen, it still needed a heating stage. With increased coal concentration, the furnace core temperatures in the primary air section went up firstly and then down, but the carbon in fly ash and slag showed adverse behavior. This was due to the high coal concentration corresponding to high volatile concentration leading to the timely ignition and burnout, causing higher furnace core temperature in the primary air section and decreased carbon in fly ash and slag. Corresponding to the highest furnace core temperature in the primary air section and the lowest carbon in fly ash and slag, the optimal pulverized coal concentration of anthracite and bituminous was 0.796-0.810Â kg coal/kg air and 0.586-0.607Â kg coal/kg air, respectively. In addition, with increased pulverized coal concentration, the NOx emissions reduced quickly with a slight decrease in the range of the optimal pulverized coal concentration.

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  • Tan, Houzhang & Niu, Yanqing & Wang, Xuebin & Xu, Tongmo & Hui, Shien, 2011. "Study of optimal pulverized coal concentration in a four-wall tangentially fired furnace," Applied Energy, Elsevier, vol. 88(4), pages 1164-1168, April.
    • Handle: RePEc:eee:appene:v:88:y:2011:i:4:p:1164-1168
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    References listed on IDEAS

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    1. Zhou, Hao & Cen, Kefa & Fan, Jianren, 2004. "Modeling and optimization of the NOx emission characteristics of a tangentially fired boiler with artificial neural networks," Energy, Elsevier, vol. 29(1), pages 167-183.
    2. Luan, Tao & Wang, Xuedong & Hao, Yuzhen & Cheng, Lin, 2009. "Control of NO emission during coal reburning," Applied Energy, Elsevier, vol. 86(9), pages 1783-1787, September.
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    5. Yang, Yongping & Wang, Ligang & Dong, Changqing & Xu, Gang & Morosuk, Tatiana & Tsatsaronis, George, 2013. "Comprehensive exergy-based evaluation and parametric study of a coal-fired ultra-supercritical power plant," Applied Energy, Elsevier, vol. 112(C), pages 1087-1099.
    6. Li, Zixiang & Qiao, Xinqi & Miao, Zhengqing, 2021. "A novel burner arrangement scheme with annularly combined multiple airflows for wall-tangentially fired pulverized coal boiler," Energy, Elsevier, vol. 222(C).
    7. Liu, Chunlong & Li, Zhengqi & Jing, Xinjing & Xie, Yiquan & Zhang, Qinghua & Zong, Qiudong, 2014. "Experimental investigation into gas/particle flow in a down-fired 350 MWe supercritical utility boiler at different over-fire air ratios," Energy, Elsevier, vol. 64(C), pages 771-778.
    8. Kuang, Min & Li, Zhengqi & Liu, Chunlong & Zhu, Qunyi, 2013. "Experimental study on combustion and NOx emissions for a down-fired supercritical boiler with multiple-injection multiple-staging technology without overfire air," Applied Energy, Elsevier, vol. 106(C), pages 254-261.
    9. Niu, Yanqing & Yan, Bokang & Liu, Siqi & Liang, Yang & Dong, Ning & Hui, Shi'en, 2018. "Ultra-fine particulate matters (PMs) formation during air and oxy-coal combustion: Kinetics study," Applied Energy, Elsevier, vol. 218(C), pages 46-53.
    10. Jing Wang & Jingchi Yang & Fengling Yang & Fangqin Cheng, 2023. "Numerical and Experimental Investigation of the Decoupling Combustion Characteristics of a Burner with Flame Stabilizer," Energies, MDPI, vol. 16(11), pages 1-20, June.
    11. Roman I. Egorov & Alexandr S. Zaitsev & Eugene A. Salgansky, 2018. "Activation of the Fuels with Low Reactivity Using the High-Power Laser Pulses," Energies, MDPI, vol. 11(11), pages 1-8, November.
    12. Chen, Shinan & He, Boshu & He, Di & Cao, Yang & Ding, Guangchao & Liu, Xuan & Duan, Zhipeng & Zhang, Xin & Song, Jingge & Li, Xuezheng, 2017. "Numerical investigations on different tangential arrangements of burners for a 600 MW utility boiler," Energy, Elsevier, vol. 122(C), pages 287-300.
    13. Marco Torresi & Francesco Fornarelli & Bernardo Fortunato & Sergio Mario Camporeale & Alessandro Saponaro, 2017. "Assessment against Experiments of Devolatilization and Char Burnout Models for the Simulation of an Aerodynamically Staged Swirled Low-NO x Pulverized Coal Burner," Energies, MDPI, vol. 10(1), pages 1-24, January.
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