IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v72y2014icp752-759.html
   My bibliography  Save this article

Maximizing the transferred power to electric arc furnace for having maximum production

Author

Listed:
  • Samet, Haidar
  • Ghanbari, Teymoor
  • Ghaisari, Jafar

Abstract

In order to increase production of an EAF (electric arc furnace) by reduction of melting time, one can increase transferred power to the EAF. In other words a certain value of energy can be transferred to the EAF in less time. The transferred power to the EAF reduces when series reactors are utilized in order to have stable arc with desired characteristics. To compensate the reduced transferred power, the secondary voltage of the EAF transformer should be increased by tap changing of the transformer. On the other hand, after any tap changing of the EAF transformer, improved arc stability is degraded. Therefore, the series reactor and EAF transformer tap changing should be simultaneously determined to achieve arc with desired characteristics. In this research, three approaches are proposed to calculate the EAF system parameters, by which the optimal set-points of the different series reactor and EAF transformer taps are determined. The electric characteristics relevant to the EAF for the all transformer and series reactor taps with and without SVC (static VAr compensator) are plotted and based on these graphs the optimal set-points are tabulated. Finally, an economic evaluation is also presented for the methods.

Suggested Citation

  • Samet, Haidar & Ghanbari, Teymoor & Ghaisari, Jafar, 2014. "Maximizing the transferred power to electric arc furnace for having maximum production," Energy, Elsevier, vol. 72(C), pages 752-759.
    • Handle: RePEc:eee:energy:v:72:y:2014:i:c:p:752-759
    DOI: 10.1016/j.energy.2014.05.105
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544214006860
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2014.05.105?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kirschen, Marcus & Badr, Karim & Pfeifer, Herbert, 2011. "Influence of direct reduced iron on the energy balance of the electric arc furnace in steel industry," Energy, Elsevier, vol. 36(10), pages 6146-6155.
    2. Arens, Marlene & Worrell, Ernst & Schleich, Joachim, 2012. "Energy intensity development of the German iron and steel industry between 1991 and 2007," Energy, Elsevier, vol. 45(1), pages 786-797.
    3. Kovačič, Miha & Šarler, Božidar, 2014. "Genetic programming prediction of the natural gas consumption in a steel plant," Energy, Elsevier, vol. 66(C), pages 273-284.
    4. Hasanbeigi, Ali & Morrow, William & Sathaye, Jayant & Masanet, Eric & Xu, Tengfang, 2013. "A bottom-up model to estimate the energy efficiency improvement and CO2 emission reduction potentials in the Chinese iron and steel industry," Energy, Elsevier, vol. 50(C), pages 315-325.
    5. Cui, Qiang & Kuang, Hai-bo & Wu, Chun-you & Li, Ye, 2014. "The changing trend and influencing factors of energy efficiency: The case of nine countries," Energy, Elsevier, vol. 64(C), pages 1026-1034.
    6. Pardo, Nicolás & Moya, José Antonio, 2013. "Prospective scenarios on energy efficiency and CO2 emissions in the European Iron & Steel industry," Energy, Elsevier, vol. 54(C), pages 113-128.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sheinbaum-Pardo, Claudia, 2016. "Decomposition analysis from demand services to material production: The case of CO2 emissions from steel produced for automobiles in Mexico," Applied Energy, Elsevier, vol. 174(C), pages 245-255.
    2. Bhadbhade, Navdeep & Zuberi, M. Jibran S. & Patel, Martin K., 2019. "A bottom-up analysis of energy efficiency improvement and CO2 emission reduction potentials for the swiss metals sector," Energy, Elsevier, vol. 181(C), pages 173-186.
    3. Pusnik, M. & Al-Mansour, F. & Sucic, B. & Cesen, M., 2017. "Trends and prospects of energy efficiency development in Slovenian industry," Energy, Elsevier, vol. 136(C), pages 52-62.
    4. Brunke, Jean-Christian & Blesl, Markus, 2014. "A plant-specific bottom-up approach for assessing the cost-effective energy conservation potential and its ability to compensate rising energy-related costs in the German iron and steel industry," Energy Policy, Elsevier, vol. 67(C), pages 431-446.
    5. Sun, Yongqi & Shen, Hongwei & Wang, Hao & Wang, Xidong & Zhang, Zuotai, 2014. "Experimental investigation and modeling of cooling processes of high temperature slags," Energy, Elsevier, vol. 76(C), pages 761-767.
    6. Haendel, Michael & Hirzel, Simon & Süß, Marlene, 2022. "Economic optima for buffers in direct reduction steelmaking under increasing shares of renewable hydrogen," Renewable Energy, Elsevier, vol. 190(C), pages 1100-1111.
    7. Bożena Gajdzik & Radosław Wolniak & Wies Grebski, 2023. "Process of Transformation to Net Zero Steelmaking: Decarbonisation Scenarios Based on the Analysis of the Polish Steel Industry," Energies, MDPI, vol. 16(8), pages 1-36, April.
    8. Stefan Vögele & Dirk Rübbelke & Kristina Govorukha & Matthias Grajewski, 2020. "Socio-technical scenarios for energy-intensive industries: the future of steel production in Germany," Climatic Change, Springer, vol. 162(4), pages 1763-1778, October.
    9. Xu, Bin & Lin, Boqiang, 2016. "Assessing CO2 emissions in China’s iron and steel industry: A dynamic vector autoregression model," Applied Energy, Elsevier, vol. 161(C), pages 375-386.
    10. Sinha, Rakesh Kumar & Chaturvedi, Nitin Dutt, 2019. "A review on carbon emission reduction in industries and planning emission limits," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    11. Zhang, Qi & Zhao, Xiaoyu & Lu, Hongyou & Ni, Tuanjie & Li, Yu, 2017. "Waste energy recovery and energy efficiency improvement in China’s iron and steel industry," Applied Energy, Elsevier, vol. 191(C), pages 502-520.
    12. Wang, Peng & Zhao, Shen & Dai, Tao & Peng, Kun & Zhang, Qi & Li, Jiashuo & Chen, Wei-Qiang, 2022. "Regional disparities in steel production and restrictions to progress on global decarbonization: A cross-national analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    13. Broeren, M.L.M. & Saygin, D. & Patel, M.K., 2014. "Forecasting global developments in the basic chemical industry for environmental policy analysis," Energy Policy, Elsevier, vol. 64(C), pages 273-287.
    14. Sébastien Pissot & Henrik Thunman & Peter Samuelsson & Martin Seemann, 2021. "Production of Negative-Emissions Steel Using a Reducing Gas Derived from DFB Gasification," Energies, MDPI, vol. 14(16), pages 1-32, August.
    15. Julian Suer & Marzia Traverso & Nils Jäger, 2022. "Review of Life Cycle Assessments for Steel and Environmental Analysis of Future Steel Production Scenarios," Sustainability, MDPI, vol. 14(21), pages 1-22, October.
    16. Zhang, Qi & Xu, Jin & Wang, Yujie & Hasanbeigi, Ali & Zhang, Wei & Lu, Hongyou & Arens, Marlene, 2018. "Comprehensive assessment of energy conservation and CO2 emissions mitigation in China’s iron and steel industry based on dynamic material flows," Applied Energy, Elsevier, vol. 209(C), pages 251-265.
    17. Wu, Junnian & Pu, Guangying & Guo, Yan & Lv, Jingwen & Shang, Jiangwei, 2018. "Retrospective and prospective assessment of exergy, life cycle carbon emissions, and water footprint for coking network evolution in China," Applied Energy, Elsevier, vol. 218(C), pages 479-493.
    18. Zeng, Yujiao & Xiao, Xin & Li, Jie & Sun, Li & Floudas, Christodoulos A. & Li, Hechang, 2018. "A novel multi-period mixed-integer linear optimization model for optimal distribution of byproduct gases, steam and power in an iron and steel plant," Energy, Elsevier, vol. 143(C), pages 881-899.
    19. Rehfeldt, M. & Worrell, E. & Eichhammer, W. & Fleiter, T., 2020. "A review of the emission reduction potential of fuel switch towards biomass and electricity in European basic materials industry until 2030," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    20. Chen, Wenying & Yin, Xiang & Ma, Ding, 2014. "A bottom-up analysis of China’s iron and steel industrial energy consumption and CO2 emissions," Applied Energy, Elsevier, vol. 136(C), pages 1174-1183.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:72:y:2014:i:c:p:752-759. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.