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Strategies for the Resilience of Power-Coal Supply Chains in Low-Carbon Energy Transition: A System Dynamics Model and Scenario Analysis of China up to 2060

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  • Zehua Yu

    (State Key Laboratory of Power Systems, Department of Energy and Power Engineering, Tsinghua-BP Clean Energy Research and Education Centre, Tsinghua University, Beijing 100084, China
    Tsinghua-Rio Tinto Joint Research Centre for Resources, Energy and Sustainable Development, International Joint Laboratory on Low Carbon Clean Energy Innovation, Laboratory for Low Carbon Energy, Tsinghua University, Beijing 100084, China)

  • Zheng Li

    (State Key Laboratory of Power Systems, Department of Energy and Power Engineering, Tsinghua-BP Clean Energy Research and Education Centre, Tsinghua University, Beijing 100084, China
    Tsinghua-Rio Tinto Joint Research Centre for Resources, Energy and Sustainable Development, International Joint Laboratory on Low Carbon Clean Energy Innovation, Laboratory for Low Carbon Energy, Tsinghua University, Beijing 100084, China)

  • Linwei Ma

    (State Key Laboratory of Power Systems, Department of Energy and Power Engineering, Tsinghua-BP Clean Energy Research and Education Centre, Tsinghua University, Beijing 100084, China
    Tsinghua-Rio Tinto Joint Research Centre for Resources, Energy and Sustainable Development, International Joint Laboratory on Low Carbon Clean Energy Innovation, Laboratory for Low Carbon Energy, Tsinghua University, Beijing 100084, China)

Abstract

The global trends of coal phase-out in response to climate change are meeting obstacles in China, where a stable operation of power-coal supply chains remains essential. How to guarantee the resilience of these supply chains during the low-carbon transition becomes a critical issue. This study aims to recommend corresponding strategies by modelling and analysis. A system dynamics model was developed to analyze scenarios of China’s power-coal supply from 2021 to 2060. The results indicated that, firstly, the capacity redundancy of coal mines will increase from 1.13 to 1.32 before 2045, with the rising power-coal demand and its volatility, followed by a sharp decrease after that, in which demand falls in all scenarios. Secondly, increasing coal stock in each link can effectively reduce capacity redundancy of coal mines and imports during the period of rising demand, resulting in 250 million tons of coal mine capacity reduction, but will lead to an opposite result when demand falls. Finally, under high demand fluctuations, coal transport capacity will become a key constraint. It is recommended that China must improve the capacity redundancy of coal mines, coal stock, and coal transport in the near-term, as well as enhance long-term planning to carefully coordinate these factors during the whole process of low-carbon transition.

Suggested Citation

  • Zehua Yu & Zheng Li & Linwei Ma, 2023. "Strategies for the Resilience of Power-Coal Supply Chains in Low-Carbon Energy Transition: A System Dynamics Model and Scenario Analysis of China up to 2060," Sustainability, MDPI, vol. 15(9), pages 1-19, April.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:9:p:7154-:d:1132203
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    References listed on IDEAS

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    1. Yang, Qing & Zhang, Lei & Zhang, Jinsuo & Zou, Shaohui, 2021. "System simulation and policy optimization of China's coal production capacity deviation in terms of the economy, environment, and energy security," Resources Policy, Elsevier, vol. 74(C).
    2. Koot, Martijn & Wijnhoven, Fons, 2021. "Usage impact on data center electricity needs: A system dynamic forecasting model," Applied Energy, Elsevier, vol. 291(C).
    3. Chong, ChinHao & Ma, Linwei & Li, Zheng & Ni, Weidou & Song, Shizhong, 2015. "Logarithmic mean Divisia index (LMDI) decomposition of coal consumption in China based on the energy allocation diagram of coal flows," Energy, Elsevier, vol. 85(C), pages 366-378.
    4. Wang, Xiaofei & Miao, Chenglin & Wang, Chongmei & Yin, Dawei & Chen, Shaojie & Chen, Lei & Li, Ke, 2022. "Coal production capacity allocation based on efficiency perspective—taking production mines in Shandong Province as an example," Energy Policy, Elsevier, vol. 171(C).
    5. Zhang, Yanfang & Nie, Rui & Shi, Xunpeng & Qian, Xiangyan & Wang, Ke, 2019. "Can energy-price regulations smooth price fluctuations? Evidence from China’s coal sector," Energy Policy, Elsevier, vol. 128(C), pages 125-135.
    6. Lin, Bo-qiang & Liu, Jiang-hua, 2010. "Estimating coal production peak and trends of coal imports in China," Energy Policy, Elsevier, vol. 38(1), pages 512-519, January.
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