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Charging station forecasting and scenario analysis in China

Author

Listed:
  • Liu, Bingchun
  • Song, Jiangji
  • Wang, Qingshan
  • Xu, Yan
  • Liu, Yifan

Abstract

China's electric vehicle industry has gained momentum due to multiple factors, but there is still a gap in demand for charging stations. China's subsidy policy for EVs is gradually withdrawing from the market and increasing subsidies for charging facilities to stabilize the growth of EVs. Taking the number of EVs as the decision parameter, this paper proposes a multi-factor combination prediction model of grey correlation and long and short-term memory. The model predicts that the number of EVs in China will reach 1.02 billion by 2030. The importance of factors is discussed qualitatively through scenario setting analysis of EV electricity consumption and power supply. It is found that charging stations in China will show varying degrees of growth from 2021 to 2030. Finally, corresponding suggestions are put forward for charging stations, including charging subsidies, technology R&D innovation policies, and licensing quotas.

Suggested Citation

  • Liu, Bingchun & Song, Jiangji & Wang, Qingshan & Xu, Yan & Liu, Yifan, 2023. "Charging station forecasting and scenario analysis in China," Transport Policy, Elsevier, vol. 139(C), pages 87-98.
    • Handle: RePEc:eee:trapol:v:139:y:2023:i:c:p:87-98
    DOI: 10.1016/j.tranpol.2023.05.012
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    References listed on IDEAS

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    2. Cao, Jianing & Han, Yuhang & Pan, Nan & Zhang, Jingcheng & Yang, Junwei, 2024. "A data-driven approach to urban charging facility expansion based on bi-level optimization: A case study in a Chinese city," Energy, Elsevier, vol. 300(C).

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