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Energy-Saving Potential of China’s Steel Industry According to Its Development Plan

Author

Listed:
  • Kun He

    (School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China)

  • Li Wang

    (School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
    Beijing Engineering Research Center for Energy Saving & Environmental Protection, Beijing 100083, China)

  • Hongliang Zhu

    (Hanbao Steel Energy Center, Handan 056015, China)

  • Yulong Ding

    (Birmingham Centre for Energy Storage, School of Chemical Engineering, University of Birmingham, Birmingham B15 2TT, UK)

Abstract

The energy consumption of China’s steel industry accounted for 53% of the global steel industry energy consumption in 2014. This paper aims to analyze the energy saving potential of China’s steel industry, according to its development plan of the next decade, and find the key of energy conservation. A multivariate energy intensity (MEI) model is developed for energy saving potential analysis based on the research on China’s energy statistics indexes and methods, which is able to capture the impacts of production routes, technology progress, industrial concentration, energy structure, and electricity (proportion and generation efficiency). Different scenarios have been set to describe future policy measures in relation to the development of the iron and steel industry. Results show that an increasing scrap ratio (SR) has the greatest energy saving effect of 16.8% when compared with 2014, and the maximum energy saving potential reaches 23.7% after counting other factors. When considering coal consumption of power generation, the energy saving effect of increasing SR drops to 7.9%, due to the increase on the proportion of electricity in total energy consumption, and the maximum energy saving potential is 15.5%, and they can increase to 10.1% and 17.5%, respectively, with improving China’s power generation technology level.

Suggested Citation

  • Kun He & Li Wang & Hongliang Zhu & Yulong Ding, 2018. "Energy-Saving Potential of China’s Steel Industry According to Its Development Plan," Energies, MDPI, vol. 11(4), pages 1-16, April.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:4:p:948-:d:141372
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    References listed on IDEAS

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    1. Lin, Boqiang & Wu, Ya & Zhang, Li, 2011. "Estimates of the potential for energy conservation in the Chinese steel industry," Energy Policy, Elsevier, vol. 39(6), pages 3680-3689, June.
    2. Stefan Nabernegg & Birgit Bednar-Friedl & Fabian Wagner & Thomas Schinko & Janusz Cofala & Yadira Mori Clement, 2017. "The Deployment of Low Carbon Technologies in Energy Intensive Industries: A Macroeconomic Analysis for Europe, China and India," Energies, MDPI, vol. 10(3), pages 1-26, March.
    3. Proença, Sara & St. Aubyn, Miguel, 2013. "Hybrid modeling to support energy-climate policy: Effects of feed-in tariffs to promote renewable energy in Portugal," Energy Economics, Elsevier, vol. 38(C), pages 176-185.
    4. Hasanbeigi, Ali & Morrow, William & Sathaye, Jayant & Masanet, Eric & Xu, Tengfang, 2013. "A bottom-up model to estimate the energy efficiency improvement and CO2 emission reduction potentials in the Chinese iron and steel industry," Energy, Elsevier, vol. 50(C), pages 315-325.
    5. He, Feng & Zhang, Qingzhi & Lei, Jiasu & Fu, Weihui & Xu, Xiaoning, 2013. "Energy efficiency and productivity change of China’s iron and steel industry: Accounting for undesirable outputs," Energy Policy, Elsevier, vol. 54(C), pages 204-213.
    6. Fujimori, Shinichiro & Masui, Toshihiko & Matsuoka, Yuzuru, 2014. "Development of a global computable general equilibrium model coupled with detailed energy end-use technology," Applied Energy, Elsevier, vol. 128(C), pages 296-306.
    7. Ye Duan & Nan Li & Hailin Mu & Shusen Gui, 2017. "Research on CO 2 Emission Reduction Mechanism of China’s Iron and Steel Industry under Various Emission Reduction Policies," Energies, MDPI, vol. 10(12), pages 1-24, December.
    8. Murphy, Rose & Jaccard, Mark, 2011. "Energy efficiency and the cost of GHG abatement: A comparison of bottom-up and hybrid models for the US," Energy Policy, Elsevier, vol. 39(11), pages 7146-7155.
    9. Dai, Hancheng & Mischke, Peggy & Xie, Xuxuan & Xie, Yang & Masui, Toshihiko, 2016. "Closing the gap? Top-down versus bottom-up projections of China’s regional energy use and CO2 emissions," Applied Energy, Elsevier, vol. 162(C), pages 1355-1373.
    10. Zhang, Shaohui & Worrell, Ernst & Crijns-Graus, Wina & Wagner, Fabian & Cofala, Janusz, 2014. "Co-benefits of energy efficiency improvement and air pollution abatement in the Chinese iron and steel industry," Energy, Elsevier, vol. 78(C), pages 333-345.
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