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Collaborative Scheduling between OSPPs and Gasholders in Steel Mill under Time-of-Use Power Price

Author

Listed:
  • Juxian Hao

    (School of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing 100083, China)

  • Xiancong Zhao

    (School of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing 100083, China)

  • Hao Bai

    (School of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing 100083, China)

Abstract

Byproduct gases generated during steel production process are the main fuels for on-site power plants (OSPPs) in steel enterprises. Recently, with the implementation of time-of-use (TOU) power price in China, increasing attention has been paid to the collaborative scheduling between OSPPs and gasholders. However, the load shifting potential of OSPPs has seldom been discussed in previous studies. In this paper, a mixed integer linear programming (MILP)-based scheduling model is built to evaluate the load shifting potential and the corresponding economic benefits. A case study is conducted on two steel enterprises with different configurations of OSPPs, and the optimal operation strategy is also discussed.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:8:p:1174-:d:107619
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    References listed on IDEAS

    as
    1. He, Kun & Zhu, Hongliang & Wang, Li, 2015. "A new coal gas utilization mode in China’s steel industry and its effect on power grid balancing and emission reduction," Applied Energy, Elsevier, vol. 154(C), pages 644-650.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Gong, Chengzhu & Tang, Kai & Zhu, Kejun & Hailu, Atakelty, 2016. "An optimal time-of-use pricing for urban gas: A study with a multi-agent evolutionary game-theoretic perspective," Applied Energy, Elsevier, vol. 163(C), pages 283-294.
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    Cited by:

    1. 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.

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