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Multi-energy synergistic optimization in steelmaking process based on energy hub concept

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Abstract

The production process of iron and steel is accompanied by a large amount of energy production and consumption. Optimal scheduling and utilization of these energies within energy systems are crucial to realize a reduction in the cost, energy use, and CO2 emissions. However, it is difficult to model and schedule energy usage within steel works because different types of energy and devices are involved. The energy hub (EH), as a universal modeling frame, is widely used in multi-energy systems to improve its efficiency, flexibility, and reliability. This paper proposed an efficient multi-layer model based on the EH concept, which is designed to systematically model the energy system and schedule energy within steelworks to meet the energy demand. Besides, to simulate the actual working conditions of the energy devices, the method of fitting the curve is used to describe the efficiency of the energy devices. Moreover, to evaluate the applicability of the proposed model, a case study is conducted to minimize both the economic operation cost and CO2 emissions. The optimal results demonstrated that the model is suitable for energy systems within steel works. Further, the economic operation cost decreased by 3.41%, and CO2 emissions decreased by approximately 3.67%.

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References

  1. Z.B. Hu, D.F. He, K. Feng, P.Z. Liu, and Y.W. Jia, Optimal design model of the energy systems in iron and steel enterprises, Appl. Sci., 9(2019), No. 22, art. No. 4778.

  2. J.H. Kim, H.S. Yi, and C. Han, A novel MILP model for plantwide multiperiod optimization of byproduct gas supply system in the iron- and steel-making process, Chem. Eng. Res. Des., 81(2003), No. 8, p. 1015.

    Article  CAS  Google Scholar 

  3. B. Çiftçi, Potential Game Changers for the Future of Steelmaking, World Steel Association, 2017 [2020-10-11]. https://www.worldsteel.org/media-centre/blog/2017/blog-out-look-ferrous-scrap.html

  4. P. Mancarella, MES (multi-energy systems): An overview of concepts and evaluation models, Energy, 65(2014), p. 1.

    Article  Google Scholar 

  5. R.Y. Yin, Review on the study of metallurgical process engineering, Int. J. Miner. Metall. Mater., 28(2021), No. 8, p. 1253.

    Google Scholar 

  6. H. Ahmadisedigh and L. Gosselin, Combined heating and cooling networks with waste heat recovery based on energy hub concept, Appl. Energy, 253(2019), art. No. 113495.

  7. M. Geidl, Integrated Modeling and Optimization of Multi-Carrier Energy Systems [Dissertation], Swiss Federal Institute of Technology in Zurich, Zurich, 2007.

    Google Scholar 

  8. H.N. Kong, E.S. Qi, H. Li, G. Li, and X. Zhang, An MILP model for optimization of byproduct gases in the integrated iron and steel plant, Appl. Energy, 87(2010), No. 7, p. 2156.

    Article  CAS  Google Scholar 

  9. X.C. Zhao, H. Bai, X. Lu, Q. Shi, and J.H. Han, A MILP model concerning the optimisation of penalty factors for the short-term distribution of byproduct gases produced in the iron and steel making process, Appl. Energy, 148(2015), p. 142.

    Article  CAS  Google Scholar 

  10. H.N. Kong, A green mixed integer linear programming model for optimization of byproduct gases in iron and steel industry, J. Iron Steel Res. Int., 22(2015), No. 8, p. 681.

    Article  Google Scholar 

  11. Q. Zhang, H. Li, J.L. Ma, H.Y. Xu, B.Y. Yu, G. Wang, and S. Jiang, Dynamic forecasting and optimal scheduling of byproduct gases in integrated iron and steel works, J. Iron Steel Res. Int., 26(2019), No. 5, p. 529.

    Article  CAS  Google Scholar 

  12. X.C. Zhao, H. Bai, Q. Shi, X. Lu, and Z.H. Zhang, Optimal scheduling of a byproduct gas system in a steel plant considering time-of-use electricity pricing, Appl. Energy, 195(2017), p. 100.

    Article  Google Scholar 

  13. X.C. Zhao, H. Bai, and J.X. Hao, Research on the load shifting potential of on-site power plants with byproduct gasholders in steel enterprises under time-of-use power price, Energy Procedia, 142(2017), p. 2704.

    Article  Google Scholar 

  14. Q. Zhang, W. Ti, T. Du, and J.J. Cai, Coupling model of gas-steam-electricity and its application in steel works, CIESC J., 62(2011), No. 3, p. 753.

    CAS  Google Scholar 

  15. Z.Q. Wei, X.Q. Zhai, Q. Zhang, G. Yang, T. Du, and J.Q. Wei, A MINLP model for multi-period optimization considering couple of gas-steam-electricity and time of use electricity price in steel plant, Appl. Therm. Eng., 168(2020), art. No. 114834.

  16. Y.J. Zeng and Y.G. Sun, Multiperiod optimal planning of steam power system for steel plants under time-of-use power price, [in] Proceeding of the 11th World Congress on Intelligent Control and Automation, Shenyang, 2014, p. 4875.

  17. Y.J. Zeng, X. Xiao, J. Li, L. Sun, C.A. Floudas, and H.C. Li, 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, 143(2018), p. 881.

    Article  CAS  Google Scholar 

  18. M. Mohammadi, Y. Noorollahi, B. Mohammadi-Ivatloo, and H. Yousefi, Energy hub: From a model to a concept — A review, Renewable Sustainable Energy Rev., 80(2017), p. 1512.

    Article  Google Scholar 

  19. M. Mohammadi, Y. Noorollahi, B. Mohammadi-Ivatloo, M. Hosseinzadeh, H. Yousefi, and S.T. Khorasani, Optimal management of energy hubs and smart energy hubs — A review, Renewable Sustainable Energy Rev., 89(2018), p. 33.

    Article  Google Scholar 

  20. H. Sadeghi, M. Rashidinejad, M. Moeini-Aghtaie, and A. Abdollahi, The energy hub: An extensive survey on the state-of-the-art, Appl. Therm. Eng., 161(2019), art. No. 114071.

  21. G. Mavromatidis, K. Orehounig, L.A. Bollinger, M. Hohmann, J.F. Marquant, S. Miglani, B. Morvaj, P. Murray, C. Waibel, D.H. Wang, and J. Carmeliet, Ten questions concerning modeling of distributed multi-energy systems, Build. Environ., 165(2019), art. No. 106372.

  22. Y. Wang, N. Zhang, Z.Y. Zhuo, C.Q. Kang, and D. Kirschen, Mixed-integer linear programming-based optimal configuration planning for energy hub: Starting from scratch, Appl. Energy, 210(2018), p. 1141.

    Article  Google Scholar 

  23. X. Hu, S.K. Tang, H.Z. Cheng, L. Wang, Y.Q. Liu, and Y. Cai, Integrated modeling and planning of district multi-carrier energy systems, [in] 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2), Beijing, 2017, p. 1.

  24. X.P. Zhang, M. Shahidehpour, A. Alabdulwahab, and A. Abusorrah, Optimal expansion planning of energy hub with multiple energy infrastructures, IEEE Trans. Smart Grid, 6(2015), No. 5, p. 2302.

    Article  Google Scholar 

  25. T.H. Liu, D.D. Zhang, S.Y. Wang, and T. Wu, Standardized modelling and economic optimization of multi-carrier energy systems considering energy storage and demand response, Energy Convers. Manage., 182(2019), p. 126.

    Article  Google Scholar 

  26. G.T. Ayele, P. Haurant, B. Laumert, and B. Lacarrière, An extended energy hub approach for load flow analysis of highly coupled district energy networks: Illustration with electricity and heating, Appl. Energy, 212(2018), p. 850.

    Article  Google Scholar 

  27. S.D. Beigvand, H. Abdi, and M. La Scala, A general model for energy hub economic dispatch, Appl. Energy, 190(2017), p. 1090.

    Article  Google Scholar 

  28. S.D. Beigvand, H. Abdi, and M. La Scala, Economic dispatch of multiple energy carriers, Energy, 138(2017), p. 861.

    Article  Google Scholar 

  29. A. Maroufmashat, A. Elkamel, M. Fowler, S. Sattari, R. Roshandel, A. Hajimiragha, S. Walker, and E. Entchev, Modeling and optimization of a network of energy hubs to improve economic and emission considerations, Energy, 93(2015), p. 2546.

    Article  Google Scholar 

  30. A. Bostan, M.S. Nazar, M. Shafie-Khah, and J.P.S. Catalão, Optimal scheduling of distribution systems considering multiple downward energy hubs and demand response programs, Energy, 190(2020), art. No. 116349.

  31. V. Davatgaran, M. Saniei, and S.S. Mortazavi, Smart distribution system management considering electrical and thermal demand response of energy hubs, Energy, 169(2019), p. 38.

    Article  Google Scholar 

  32. M. Mostafavi Sani, A. Noorpoor, and M. Shafie-Pour Motlagh, Optimal model development of energy hub to supply water, heating and electrical demands of a cement factory, Energy, 177(2019), p. 574.

    Article  Google Scholar 

  33. M. Ghorab, Energy hubs optimization for smart energy network system to minimize economic and environmental impact at Canadian community, Appl. Therm. Eng., 151(2019), p. 214.

    Article  Google Scholar 

  34. Y.M. Zhang, Y.Q. Han, J.Y. Yan, and R.L. Chen, Thermodynamic analysis of compound cycle system for automotive waste heat recovery and air conditioning refrigeration, Energy Convers. Manage., 168(2018), p. 32.

    Article  CAS  Google Scholar 

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Acknowledgements

This work was financially supported by the National Key Research and Development Program of China (No. 2020YFB1711102) and the National Natural Science Foundation of China (No. 51874095). The authors gratefully acknowledge the reviewers and editors for their fruitful comments.

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Correspondence to Qi Zhang.

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Liu, S., Xie, S. & Zhang, Q. Multi-energy synergistic optimization in steelmaking process based on energy hub concept. Int J Miner Metall Mater 28, 1378–1386 (2021). https://doi.org/10.1007/s12613-021-2281-7

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  • DOI: https://doi.org/10.1007/s12613-021-2281-7

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