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A Mixed Integer Linear Programming Model for the Optimization of Steel Waste Gases in Cogeneration: A Combined Coke Oven and Converter Gas Case Study

Author

Listed:
  • Sergio García García

    (EDP, Energias de Portugal, Plaza del Fresno, 2, 33007 Oviedo, Spain)

  • Vicente Rodríguez Montequín

    (Department of Mining Exploitation and Prospecting, University of Oviedo, C/Independencia 3, 33004 Oviedo, Spain)

  • Henar Morán Palacios

    (Department of Mining Exploitation and Prospecting, University of Oviedo, C/Independencia 3, 33004 Oviedo, Spain)

  • Adriano Mones Bayo

    (Department of Mining Exploitation and Prospecting, University of Oviedo, C/Independencia 3, 33004 Oviedo, Spain)

Abstract

Off-gas is one of the by-products of the steelmaking process. Its potential energy can be transformed into heat and electricity by means of cogeneration. A case study using a coke oven and Linz–Donawitz converter gas is presented. This work addresses the gas allocation problem for a cogeneration system producing steam and electricity. In the studied facility, located in northern Spain, the annual production of the plant requires 95,000 MWh of electrical energy and 525,000 MWh of thermal energy. The installed electrical and thermal power is 20.4 MW and 81 MW, respectively. A mixed integer linear programming model is built to optimize gas allocation, thus maximizing its benefits. This model is applied to a 24-h scenario with real data from the plant, where gas allocation decision-making was performed by the plant operators. Application of the model generated profit in a scenario where there were losses, increasing benefits by 16.9%. A sensitivity analysis is also performed. The proposed model is useful not only from the perspective of daily plant operation but also as a tool to simulate different design scenarios, such as the capacity of gasholders.

Suggested Citation

  • Sergio García García & Vicente Rodríguez Montequín & Henar Morán Palacios & Adriano Mones Bayo, 2020. "A Mixed Integer Linear Programming Model for the Optimization of Steel Waste Gases in Cogeneration: A Combined Coke Oven and Converter Gas Case Study," Energies, MDPI, vol. 13(15), pages 1-25, July.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:15:p:3781-:d:388847
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    References listed on IDEAS

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    1. Kong, Haining & Qi, Ershi & Li, Hui & Li, Gang & Zhang, Xing, 2010. "An MILP model for optimization of byproduct gases in the integrated iron and steel plant," Applied Energy, Elsevier, vol. 87(7), pages 2156-2163, July.
    2. de Oliveira Junior, Valter B. & Pena, João G. Coelho & Salles, José L. Félix, 2016. "An improved plant-wide multiperiod optimization model of a byproduct gas supply system in the iron and steel-making process," Applied Energy, Elsevier, vol. 164(C), pages 462-474.
    3. 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.
    4. He, Kun & Wang, Li, 2017. "A review of energy use and energy-efficient technologies for the iron and steel industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1022-1039.
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    6. Quader, M. Abdul & Ahmed, Shamsuddin & Ghazilla, Raja Ariffin Raja & Ahmed, Shameem & Dahari, Mahidzal, 2015. "A comprehensive review on energy efficient CO2 breakthrough technologies for sustainable green iron and steel manufacturing," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 594-614.
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    Cited by:

    1. Sergio García García & Vicente Rodríguez Montequín & Marina Díaz Piloñeta & Susana Torno Lougedo, 2021. "Multi-Objective Optimization of Steel Off-Gas in Cogeneration Using the ε-Constraint Method: A Combined Coke Oven and Converter Gas Case Study," Energies, MDPI, vol. 14(10), pages 1-21, May.
    2. Llera, Rocio & Vigil, Miguel & Díaz-Díaz, Sara & Martínez Huerta, Gemma Marta, 2022. "Prospective environmental and techno-economic assessment of steam production by means of heat pipes in the steel industry," Energy, Elsevier, vol. 239(PD).

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