Skip to main content

Advertisement

SpringerLink
Log in

Mechanism and application of an online intelligent evaluation model for energy consumption of a reheating furnace

  • Original Paper
  • Published:
Journal of Iron and Steel Research International Aims and scope Submit manuscript

Abstract

An online model was proposed to identify the reasons behind changes in the energy consumption of the reheating furnace of a steel processing plant. The heat conversion of the furnace was analyzed and integrated with the fuel consumption of the furnace to obtain a model of the energy consumption. Combined with the mechanism analysis, the basic parameters affecting energy consumption were determined, and four key influencing factors were obtained: furnace output, furnace charging temperature, furnace tapping temperature, and steel type. The specific calculation method of the contribution of each influencing factor was derived to define the conditions of the baseline energy consumption, while the online data were used to calculate the energy value and the actual performance value of the baseline energy consumption. The contribution of each influencing factor was determined through normalization. The cloud platform was used for database reconstruction and programming to realize the online intelligent evaluation of the energy consumption of the reheating furnace. Finally, a case study of the evaluation of the practical energy consumption of a steel rolling furnace in a steel plant was presented. The intelligent evaluation results were quantified and displayed online, and the performance of the system in reducing production line energy consumption was demonstrated.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. B. Dou, Contemporary Economics 24 (2007) No. 8, 80–82.

    Google Scholar 

  2. L. Yu, Metallurgical Power (2019) No. 3, 8–11.

    Google Scholar 

  3. Z.G. Wen, Y.H. Wang, H.F. Li, Y. Tao, D. De Clercq, J. Environ. Manage. 246 (2019) 717–729.

    Article  Google Scholar 

  4. X.S. Xu, S.J. Yang, J. Ind. Technol. Econ. 36 (2017) No. 1, 32–40.

    Google Scholar 

  5. S. Perry, J. Klemeš, Igor Bulatov, Energy 33 (2008) 1489–1497.

    Article  Google Scholar 

  6. J. Wang, Y.W. Liu, B. Sundén, R. Yang, J. Baleta, M. Vujanović, Energ. Convers. Manage. 149 (2017) 928–936.

    Google Scholar 

  7. W.Q. Sun, Q. Wang, Z. Zheng, J.J. Cai, Energ. Convers. Manage. 213 (2020) 112828.

    Google Scholar 

  8. K. Chakravarty, S. Kumar, Energy Rep. 6 (2020) 343–349.

    Article  Google Scholar 

  9. D.A. Chen, W.R. Miao, Y. Cheng, Z.M. Liu, W.P. Ma, H. Cao, Energ. Metall. Ind. 34 (2015) No. 2, 32–34.

    Google Scholar 

  10. Q. Liu, W.D. Li, C.B. Xu, G.Y. Ma, Energ. Metall. Ind. 35 (2016) No. 4, 38–41.

    Google Scholar 

  11. H. Wang, M.H. Zhan, Q. Cao, L. Wang, Energ. Metall. Ind. 35 (2016) No. 3, 45–48.

    Google Scholar 

  12. B. Wang, Energ. Metall. Ind. 36 (2017) No. 4, 41–43.

    Google Scholar 

  13. B. Mayr, R. Prieler, M. Demuth, C. Hochenauer, Appl. Therm. Eng. 136 (2018) 492–503.

    Article  Google Scholar 

  14. S.H. Gong, Public Communication of Science & Technology 4 (2012) No. 15, 80–81.

    Google Scholar 

  15. Nation Bureau of Statistics, Total Energy Consumption of Ferrous Metal Smelting and Calendering Industry (Ten Thousand Tons of Standard Coal) https://data.stats.gov.cn/easyquery.htm?cn=C01 (Accessed: 2022-05-10).

  16. L.H. Zhu, J.F. Wang, F. Zhang, Industrial Control Computer 24 (2011) No. 5, 70+73.

  17. K. Chen, Ind. Heat. 44 (2015) No. 1, 63–65.

    Google Scholar 

  18. P.F. Li, J.H. Ge, M.L. Wang, H. Zhang, Foundry Technology 39 (2018) 1768–1771.

    Google Scholar 

  19. M.Y. Kim, Int. J. Heat Mass Transfer 50 (2007) 3740–3748.

    Article  Google Scholar 

  20. M. Landfahrer, R. Prieler, B. Mayr, H. Gerhardter, T. Zmek, J. Klarner, C. Hochenauer, Appl. Therm. Eng. 133 (2018) 39–48.

    Article  Google Scholar 

  21. C.Y. Liu, Z. Yang, L.W. Zhou, W.F. Meng, L. Xu, Metallurgical Power (2018) No. 7, 69–73.

    Google Scholar 

  22. G. Chen, Z.G. Cai, H.G. Zhang, Y. Zhang, W.M. Xiao, D. Li, in: Proceedings of the 8th National Conference on Energy and Thermal Engineering, Energy and Thermal Engineering Branch of Chinese Society for Metals, Dalian, China, 2015, pp. 691–699.

  23. V.N. Titov, S.S. Lyapin, D.D. Ivanov, V.L. Emel'yanov, Steel Transl. 36 (2006) No. 2, 4–6.

    Google Scholar 

Download references

Acknowledgements

This work was supported by the National Key Research and Development Program of China (Grant No. 2020YFB1711101) and the Anhui Provincial University Natural Science Foundation Key Project (Grant No. KJ2019A127).

Author information

Authors and Affiliations

  1. Department of Thermal Energy, School of Energy and Environment, Anhui University of Technology, Ma’anshan, 243002, Anhui, China

    Xiang-jun Bao, Jing Xu, Guang Chen, Xu Chen & Yi-ming Shen

  2. Department of Metallurgical Engineering, School of Energy and Environment, Anhui University of Technology, Ma’anshan, 243002, Auhui, China

    Jing Xu

  3. Department of Construction and Environmental Engineering, School of Architectural Engineering, Anhui University of Technology, Ma’anshan, 243002, Anhui, China

    Hong-guang Zhang

  4. Ma’anshan Iron and Steel Co., Ltd., Ma’anshan, 243003, Anhui, China

    Wei Zhai

Authors
  1. Xiang-jun Bao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jing Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Guang Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xu Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hong-guang Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yi-ming Shen
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Wei Zhai
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Guang Chen.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bao, Xj., Xu, J., Chen, G. et al. Mechanism and application of an online intelligent evaluation model for energy consumption of a reheating furnace. J. Iron Steel Res. Int. 30, 102–111 (2023). https://doi.org/10.1007/s42243-022-00801-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42243-022-00801-8

Keywords

Search

Navigation