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Optimizing the coke oven process by adjusting the temperature of the combustion chambers

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  • Farias Neto, G.W.
  • Leite, M.B.M.
  • Marcelino, T.O.A.C.
  • Carneiro, L.O.
  • Brito, K.D.
  • Brito, R.P.

Abstract

Metallurgical coke is obtained from coal and is a fuel and raw material for the iron and steel industries. However, only 15% of the world’s coal reserves have the required properties for metallurgical coke, which makes the useful coal expensive. Transforming coal into metallurgical coke is an energy-intensive endeavor, and global competition requires worldwide steelmakers to be more efficient in terms of energy consumption, therefore the optimization of the coke production process has become increasingly decisive. The objective of this study was to develop a rigorous model of the coke oven process by separately considering the coke oven, combustion chamber, and regenerative bed. In this study, the coke oven was divided into zones according to the number of available temperature measurements in each combustion chamber. The developed model using Aspen Plus™ was used primarily to obtain a more uniform combustion chamber temperature profile and to investigate the effect of the combustion chamber temperature profile on the fuel consumption. The results were validated from the plant data for temperature, flowrate, and composition. A new set of operating conditions was implemented, and the consumption of coke oven gas was reduced by approximately 12%.

Suggested Citation

  • Farias Neto, G.W. & Leite, M.B.M. & Marcelino, T.O.A.C. & Carneiro, L.O. & Brito, K.D. & Brito, R.P., 2021. "Optimizing the coke oven process by adjusting the temperature of the combustion chambers," Energy, Elsevier, vol. 217(C).
  • Handle: RePEc:eee:energy:v:217:y:2021:i:c:s0360544220325263
    DOI: 10.1016/j.energy.2020.119419
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    References listed on IDEAS

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    1. Chen, Jianjun & Yang, Siyu & Qian, Yu, 2019. "A novel path for carbon-rich resource utilization with lower emission and higher efficiency: An integrated process of coal gasification and coking to methanol production," Energy, Elsevier, vol. 177(C), pages 304-318.
    2. Qin, Shiyue & Chang, Shiyan, 2017. "Modeling, thermodynamic and techno-economic analysis of coke production process with waste heat recovery," Energy, Elsevier, vol. 141(C), pages 435-450.
    3. Qin, Shiyue & Chang, Shiyan & Yao, Qiang, 2018. "Modeling, thermodynamic and techno-economic analysis of coal-to-liquids process with different entrained flow coal gasifiers," Applied Energy, Elsevier, vol. 229(C), pages 413-432.
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    1. Qiu, Yuhang & Hui, Yunze & Zhao, Pengxiang & Cai, Cheng-Hao & Dai, Baiqian & Dou, Jinxiao & Bhattacharya, Sankar & Yu, Jianglong, 2024. "A novel image expression-driven modeling strategy for coke quality prediction in the smart cokemaking process," Energy, Elsevier, vol. 294(C).

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