IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v87y2010i7p2156-2163.html
   My bibliography  Save this article

An MILP model for optimization of byproduct gases in the integrated iron and steel plant

Author

Listed:
  • Kong, Haining
  • Qi, Ershi
  • Li, Hui
  • Li, Gang
  • Zhang, Xing

Abstract

In iron and steel industry, byproduct gases are important energy. Therefore it is significant to optimize byproduct gas distribution to achieve total cost reduction. In this paper, a dynamic mixed integer linear programming (MILP) model for multi-period optimization of byproduct gases is used to optimize byproduct gas distribution. Compared with the previous optimization model, the proposed model simultaneously optimizes the distribution of byproduct gases in byproduct gas system, cogeneration system and iron- and steel-making system. Case study shows that the proposed model finds the optimal solution in terms of total cost reduction.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:87:y:2010:i:7:p:2156-2163
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306-2619(09)00518-2
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Georgopoulou, Chariklia A. & Giannakoglou, Kyriakos C., 2009. "Two-level, two-objective evolutionary algorithms for solving unit commitment problems," Applied Energy, Elsevier, vol. 86(7-8), pages 1229-1239, July.
    2. Gopal P. Sinha & B. S. Chandrasekaran & Niloy Mitter & Goutam Dutta & Sudhir B. Singh & Aditya Roy Choudhury & P. N. Roy, 1995. "Strategic and Operational Management with Optimization at Tata Steel," Interfaces, INFORMS, vol. 25(1), pages 6-19, February.
    3. Delarue, Erik & D'haeseleer, William, 2008. "Adaptive mixed-integer programming unit commitment strategy for determining the value of forecasting," Applied Energy, Elsevier, vol. 85(4), pages 171-181, April.
    4. Ashok, S., 2006. "Peak-load management in steel plants," Applied Energy, Elsevier, vol. 83(5), pages 413-424, May.
    5. Thollander, Patrik & Mardan, Nawzad & Karlsson, Magnus, 2009. "Optimization as investment decision support in a Swedish medium-sized iron foundry - A move beyond traditional energy auditing," Applied Energy, Elsevier, vol. 86(4), pages 433-440, April.
    6. Cai, Y.P. & Huang, G.H. & Yang, Z.F. & Tan, Q., 2009. "Identification of optimal strategies for energy management systems planning under multiple uncertainties," Applied Energy, Elsevier, vol. 86(4), pages 480-495, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Porzio, Giacomo Filippo & Nastasi, Gianluca & Colla, Valentina & Vannucci, Marco & Branca, Teresa Annunziata, 2014. "Comparison of multi-objective optimization techniques applied to off-gas management within an integrated steelwork," Applied Energy, Elsevier, vol. 136(C), pages 1085-1097.
    2. Chen, Qianqian & Gu, Yu & Tang, Zhiyong & Wei, Wei & Sun, Yuhan, 2018. "Assessment of low-carbon iron and steel production with CO2 recycling and utilization technologies: A case study in China," Applied Energy, Elsevier, vol. 220(C), pages 192-207.
    3. 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.
    4. 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.
    5. Ronelly De Souza & Emanuele Nadalon & Melchiorre Casisi & Mauro Reini, 2022. "Optimal Sharing Electricity and Thermal Energy Integration for an Energy Community in the Perspective of 100% RES Scenario," Sustainability, MDPI, vol. 14(16), pages 1-39, August.
    6. Mardan, Nawzad & Klahr, Roger, 2012. "Combining optimisation and simulation in an energy systems analysis of a Swedish iron foundry," Energy, Elsevier, vol. 44(1), pages 410-419.
    7. 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.
    8. Zhao, Xiancong & Bai, Hao & Shi, Qi & Lu, Xin & Zhang, Zhihui, 2017. "Optimal scheduling of a byproduct gas system in a steel plant considering time-of-use electricity pricing," Applied Energy, Elsevier, vol. 195(C), pages 100-113.
    9. Liu, Kun & Guan, Xiaohong & Gao, Feng & Zhai, Qiaozhu & Wu, Jiang, 2015. "Self-balancing robust scheduling with flexible batch loads for energy intensive corporate microgrid," Applied Energy, Elsevier, vol. 159(C), pages 391-400.
    10. Jiang, Sheng-Long & Wang, Meihong & Bogle, I. David L., 2023. "Plant-wide byproduct gas distribution under uncertainty in iron and steel industry via quantile forecasting and robust optimization," Applied Energy, Elsevier, vol. 350(C).
    11. Zhao, Xiancong & Bai, Hao & Lu, Xin & Shi, Qi & Han, Jiehai, 2015. "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," Applied Energy, Elsevier, vol. 148(C), pages 142-158.
    12. Liu, Kun & Gao, Feng, 2017. "Scenario adjustable scheduling model with robust constraints for energy intensive corporate microgrid with wind power," Renewable Energy, Elsevier, vol. 113(C), pages 1-10.
    13. Grip, Niklas & Grip, Carl-Erik & Nilsson, Leif, 2013. "Wavelet study of dynamic variations in steel and ironmaking rest gases. Potential effect on external use," Applied Energy, Elsevier, vol. 112(C), pages 1032-1040.
    14. Sun, Wenqiang & Wang, Qiang & Zhou, Yue & Wu, Jianzhong, 2020. "Material and energy flows of the iron and steel industry: Status quo, challenges and perspectives," Applied Energy, Elsevier, vol. 268(C).
    15. Juxian Hao & Xiancong Zhao & Hao Bai, 2017. "Collaborative Scheduling between OSPPs and Gasholders in Steel Mill under Time-of-Use Power Price," Energies, MDPI, vol. 10(8), pages 1-10, August.
    16. 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.
    17. Xueying Sun & Zhuo Wang & Jingtao Hu, 2018. "Fuzzy Byproduct Gas Scheduling in the Steel Plant Considering Uncertainty and Risk Analysis," Energies, MDPI, vol. 11(10), pages 1-14, October.
    18. Porzio, Giacomo Filippo & Fornai, Barbara & Amato, Alessandro & Matarese, Nicola & Vannucci, Marco & Chiappelli, Lisa & Colla, Valentina, 2013. "Reducing the energy consumption and CO2 emissions of energy intensive industries through decision support systems – An example of application to the steel industry," Applied Energy, Elsevier, vol. 112(C), pages 818-833.
    19. Jiang, Sheng-Long & Peng, Gongzhuang & Bogle, I. David L. & Zheng, Zhong, 2022. "Two-stage robust optimization approach for flexible oxygen distribution under uncertainty in integrated iron and steel plants," Applied Energy, Elsevier, vol. 306(PB).
    20. Sandberg, Johan & Larsson, Mikael & Wang, Chuan & Dahl, Jan & Lundgren, Joakim, 2012. "A new optimal solution space based method for increased resolution in energy system optimisation," Applied Energy, Elsevier, vol. 92(C), pages 583-592.
    21. Karlsson, Magnus & Mardan, Nawzad, 2013. "Considering start-ups and shutdowns using an optimisation tool – Including a dairy production planning case study," Applied Energy, Elsevier, vol. 107(C), pages 338-349.
    22. Karlsson, Magnus, 2011. "The MIND method: A decision support for optimization of industrial energy systems - Principles and case studies," Applied Energy, Elsevier, vol. 88(3), pages 577-589, March.
    23. Golmohamadi, Hessam, 2022. "Demand-side management in industrial sector: A review of heavy industries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    24. Yáñez, María & Ortiz, Alfredo & Brunaud, Braulio & Grossmann, Ignacio E. & Ortiz, Inmaculada, 2018. "Contribution of upcycling surplus hydrogen to design a sustainable supply chain: The case study of Northern Spain," Applied Energy, Elsevier, vol. 231(C), pages 777-787.

    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. Amjady, Nima & Keynia, Farshid, 2010. "A new spinning reserve requirement forecast method for deregulated electricity markets," Applied Energy, Elsevier, vol. 87(6), pages 1870-1879, June.
    2. Aghaei, J. & Shayanfar, H.A. & Amjady, N., 2009. "Joint market clearing in a stochastic framework considering power system security," Applied Energy, Elsevier, vol. 86(9), pages 1675-1682, September.
    3. Lee, Yi-Shian & Tong, Lee-Ing, 2012. "Forecasting nonlinear time series of energy consumption using a hybrid dynamic model," Applied Energy, Elsevier, vol. 94(C), pages 251-256.
    4. Dimitroulas, Dionisios K. & Georgilakis, Pavlos S., 2011. "A new memetic algorithm approach for the price based unit commitment problem," Applied Energy, Elsevier, vol. 88(12), pages 4687-4699.
    5. Fernández-Blanco, Ricardo & Arroyo, José M. & Alguacil, Natalia, 2014. "Consumer payment minimization under uniform pricing: A mixed-integer linear programming approach," Applied Energy, Elsevier, vol. 114(C), pages 676-686.
    6. Marshman, D.J. & Chmelyk, T. & Sidhu, M.S. & Gopaluni, R.B. & Dumont, G.A., 2010. "Energy optimization in a pulp and paper mill cogeneration facility," Applied Energy, Elsevier, vol. 87(11), pages 3514-3525, November.
    7. Alexander Melnik & Kirill Ermolaev, 2020. "Strategy Context of Decision Making for Improved Energy Efficiency in Industrial Energy Systems," Energies, MDPI, vol. 13(7), pages 1-28, March.
    8. Niknam, Taher & Khodaei, Amin & Fallahi, Farhad, 2009. "A new decomposition approach for the thermal unit commitment problem," Applied Energy, Elsevier, vol. 86(9), pages 1667-1674, September.
    9. Tolis, Athanasios & Doukelis, Aggelos & Tatsiopoulos, Ilias, 2010. "Stochastic interest rates in the analysis of energy investments: Implications on economic performance and sustainability," Applied Energy, Elsevier, vol. 87(8), pages 2479-2490, August.
    10. Cai, Yanpeng & Applegate, Scott & Yue, Wencong & Cai, Jianying & Wang, Xuan & Liu, Gengyuan & Li, Chunhui, 2017. "A hybrid life cycle and multi-criteria decision analysis approach for identifying sustainable development strategies of Beijing's taxi fleet," Energy Policy, Elsevier, vol. 100(C), pages 314-325.
    11. J. F. F. Almeida & S. V. Conceição & L. R. Pinto & B. R. P. Oliveira & L. F. Rodrigues, 2022. "Optimal sales and operations planning for integrated steel industries," Annals of Operations Research, Springer, vol. 315(2), pages 773-790, August.
    12. Streckiene, Giedre & Martinaitis, Vytautas & Andersen, Anders N. & Katz, Jonas, 2009. "Feasibility of CHP-plants with thermal stores in the German spot market," Applied Energy, Elsevier, vol. 86(11), pages 2308-2316, November.
    13. Zhang, Jiyuan & Tang, Hailong & Chen, Min, 2019. "Linear substitute model-based uncertainty analysis of complicated non-linear energy system performance (case study of an adaptive cycle engine)," Applied Energy, Elsevier, vol. 249(C), pages 87-108.
    14. Changyu Zhou & Guohe Huang & Jiapei Chen, 2019. "A Type-2 Fuzzy Chance-Constrained Fractional Integrated Modeling Method for Energy System Management of Uncertainties and Risks," Energies, MDPI, vol. 12(13), pages 1-21, June.
    15. Venter, Philip van Zyl & Terblanche, Stephanus Esias & van Eldik, Martin, 2018. "Turbine investment optimisation for energy recovery plants by utilising historic steam flow profiles," Energy, Elsevier, vol. 155(C), pages 668-677.
    16. Elena Stefana & Paola Cocca & Filippo Marciano & Diana Rossi & Giuseppe Tomasoni, 2019. "A Review of Energy and Environmental Management Practices in Cast Iron Foundries to Increase Sustainability," Sustainability, MDPI, vol. 11(24), pages 1-18, December.
    17. Hajo Terbrack & Thorsten Claus & Frank Herrmann, 2021. "Energy-Oriented Production Planning in Industry: A Systematic Literature Review and Classification Scheme," Sustainability, MDPI, vol. 13(23), pages 1-32, December.
    18. Fernandez, Mayela & Li, Lin & Sun, Zeyi, 2013. "“Just-for-Peak” buffer inventory for peak electricity demand reduction of manufacturing systems," International Journal of Production Economics, Elsevier, vol. 146(1), pages 178-184.
    19. Middelberg, Arno & Zhang, Jiangfeng & Xia, Xiaohua, 2009. "An optimal control model for load shifting - With application in the energy management of a colliery," Applied Energy, Elsevier, vol. 86(7-8), pages 1266-1273, July.
    20. Changyu Zhou & Guohe Huang & Jiapei Chen, 2018. "A Multi-Objective Energy and Environmental Systems Planning Model: Management of Uncertainties and Risks for Shanxi Province, China," Energies, MDPI, vol. 11(10), pages 1-21, October.

    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:appene:v:87:y:2010:i:7:p:2156-2163. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.