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A new coal gas utilization mode in China’s steel industry and its effect on power grid balancing and emission reduction

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  • He, Kun
  • Zhu, Hongliang
  • Wang, Li

Abstract

Inspired by energy storage systems for peak load shifting (PLS), this study proposes a PLS utilization mode of electricity-generating coal gas resources for the steel industry in China. The proposed mode can help the steel industry save electricity bills (2.4%) through the introduction of a time-of-use tariff. Data of a steel enterprise are used to prove the economic benefit of the coal gas utilization mode. Given that China produces more than half of converter steel of the total production worldwide, their coal gas resources are abundant. The PLS utilization mode will have a great effect on balancing the power grid. A simulated operation model for PLS coal-fired power units is used to calculate the energy conservation and emission reduction effect of coal-fired power plants under different scenarios. The annual coal savings are 1.7–3.1%, and the annual SO2 and NOX emission reductions are 2.9–12.4% and 44.6–14.1% of the total reduction amount of the steel industry in China, respectively.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:154:y:2015:i:c:p:644-650
    DOI: 10.1016/j.apenergy.2015.05.022
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. 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.
    2. He, Xiufen & Liu, Yunong & Rehman, Ali & Wang, Li, 2021. "A novel air separation unit with energy storage and generation and its energy efficiency and economy analysis," Applied Energy, Elsevier, vol. 281(C).
    3. Wu, Xuecheng & Zhao, Liang & Zhang, Yongxin & Zhao, Lingjie & Zheng, Chenghang & Gao, Xiang & Cen, Kefa, 2016. "Cost and potential of energy conservation and collaborative pollutant reduction in the iron and steel industry in China," Applied Energy, Elsevier, vol. 184(C), pages 171-183.
    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. Xu, Bin & Lin, Boqiang, 2016. "Assessing CO2 emissions in China’s iron and steel industry: A dynamic vector autoregression model," Applied Energy, Elsevier, vol. 161(C), pages 375-386.
    6. 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.
    7. He, Xiufen & Liu, Yunong & Rehman, Ali & Wang, Li, 2022. "Feasibility and performance analysis of a novel air separation unit with energy storage and air recovery," Renewable Energy, Elsevier, vol. 195(C), pages 598-619.
    8. Xi, Han & Wu, Xiao & Chen, Xianhao & Sha, Peng, 2021. "Artificial intelligent based energy scheduling of steel mill gas utilization system towards carbon neutrality," Applied Energy, Elsevier, vol. 295(C).
    9. Wu, Yunna & Xiao, Xinli & Song, Zongyun, 2017. "Competitiveness analysis of coal industry in China: A diamond model study," Resources Policy, Elsevier, vol. 52(C), pages 39-53.

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