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Multi-objective optimization of energy distribution in steel enterprises considering both exergy efficiency and energy cost

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  • Hu, Zhengbiao
  • He, Dongfeng
  • Zhao, Hongbo

Abstract

In integrated steel works, the core objective of system energy conservation techniques is to improve energy utilization and reduce energy costs. Currently, the research on energy distribution optimization of steel enterprises considers only the energy cost of the system and ignores the energy utilization efficiency. However, energy utilization efficiency and energy cost are equally important indicators. Therefore, in this study, a multi-objective optimization model for energy systems was established, which considered minimizing energy cost of the system and maximizing exergy efficiency as the objective functions. The case results indicate that after the optimization aiming at the minimum energy cost (Scheme A) and the maximum exergy efficiency (Scheme B), the energy cost of the two schemes reduced by 24.96% and 9.60%, respectively, and the exergy efficiency increased by 1.67% and 8.65%, respectively. Although Scheme A can significantly reduce the system energy cost, the increase of exergy efficiency is limited. Scheme B is opposite to Scheme A. However, after adopting multi-objective optimization, compared with previous optimization strategies, the energy cost reduced by 22.81%, the exergy efficiency increased by 7.71%, and the energy cost and exergy efficiency of the system were found to be in a better state.

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  • Hu, Zhengbiao & He, Dongfeng & Zhao, Hongbo, 2023. "Multi-objective optimization of energy distribution in steel enterprises considering both exergy efficiency and energy cost," Energy, Elsevier, vol. 263(PB).
    • Handle: RePEc:eee:energy:v:263:y:2023:i:pb:s0360544222025099
    DOI: 10.1016/j.energy.2022.125623
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    References listed on IDEAS

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    1. Luo, Xianglong & Hu, Jiahao & Zhao, Jun & Zhang, Bingjian & Chen, Ying & Mo, Songping, 2014. "Multi-objective optimization for the design and synthesis of utility systems with emission abatement technology concerns," Applied Energy, Elsevier, vol. 136(C), pages 1110-1131.
    2. Rocco, M.V. & Colombo, E. & Sciubba, E., 2014. "Advances in exergy analysis: a novel assessment of the Extended Exergy Accounting method," Applied Energy, Elsevier, vol. 113(C), pages 1405-1420.
    3. Zhang, Qi & Gao, Jintong & Wang, Yujie & Wang, Lin & Yu, Zaihai & Song, Dayong, 2019. "Exergy-based analysis combined with LCA for waste heat recovery in coal-fired CHP plants," Energy, Elsevier, vol. 169(C), pages 247-262.
    4. Frangopoulos, Christos A., 2018. "Recent developments and trends in optimization of energy systems," Energy, Elsevier, vol. 164(C), pages 1011-1020.
    5. 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.
    6. 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.
    7. Na, Hongming & Sun, Jingchao & Qiu, Ziyang & He, Jianfei & Yuan, Yuxing & Yan, Tianyi & Du, Tao, 2021. "A novel evaluation method for energy efficiency of process industry — A case study of typical iron and steel manufacturing process," Energy, Elsevier, vol. 233(C).
    8. Song, Dan & Lin, Ling & Wu, Ye, 2019. "Extended exergy accounting for a typical cement industry in China," Energy, Elsevier, vol. 174(C), pages 678-686.
    9. 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).
    10. Hassan, Anas M. & Ayoub, M. & Eissa, M. & Musa, T. & Bruining, Hans & Farajzadeh, R., 2019. "Exergy return on exergy investment analysis of natural-polymer (Guar-Arabic gum) enhanced oil recovery process," Energy, Elsevier, vol. 181(C), pages 162-172.
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    Cited by:

    1. Wang, Xiaolei & Deng, Renxin & Yang, Yufang, 2023. "The spatiotemporal effect of factor price distortion on capacity utilization in China’s iron and steel industry," Resources Policy, Elsevier, vol. 86(PA).
    2. Li Peng & Hongjun Wu & Wenlong Cao & Qianjun Mao, 2023. "Exergy Analysis of a Shell and Tube Energy Storage Unit with Different Inclination Angles," Energies, MDPI, vol. 16(11), pages 1-17, May.

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