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Fuzzy Byproduct Gas Scheduling in the Steel Plant Considering Uncertainty and Risk Analysis

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  • Xueying Sun

    (Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
    Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Zhuo Wang

    (Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
    Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Jingtao Hu

    (Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
    Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

In the iron and steel enterprises, efficient utilization of byproduct gas is of great significance for energy conservation and emission reduction. This work presents a fuzzy optimal scheduling model for byproduct gas system. Compared with previous work, uncertainties in byproduct gas systems are taken into consideration. In our model, uncertain factors in byproduct systems are described by fuzzy variables and gasholder level constraints are formulated as fuzzy chance constraints. The economy and reliability of byproduct gas system scheduling are sensitive to different confidence levels. To provide a reference for operators to determine a proper confidence level, the risk cost is defined to quantify the risk of byproduct gas shortage and emission during the scheduling process. The best confidence level is determined through the trade-off between operation cost and risk cost. The experiment results demonstrated that the proposed method can reduce the risk and give a more reasonable optimal scheduling scheme compared with deterministic optimal scheduling.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:10:p:2727-:d:175064
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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. Zhang, Y.M. & Huang, G.H. & Lin, Q.G. & Lu, H.W., 2012. "Integer fuzzy credibility constrained programming for power system management," Energy, Elsevier, vol. 38(1), pages 398-405.
    3. 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.
    4. 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.
    5. 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.
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