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Electric vehicle batteries alone could satisfy short-term grid storage demand by as early as 2030

Author

Listed:
  • Chengjian Xu

    (Leiden University)

  • Paul Behrens

    (Leiden University)

  • Paul Gasper

    (National Renewable Energy Lab)

  • Kandler Smith

    (National Renewable Energy Lab)

  • Mingming Hu

    (Leiden University)

  • Arnold Tukker

    (Leiden University
    Netherlands Organisation for Applied Scientific Research TNO)

  • Bernhard Steubing

    (Leiden University)

Abstract

The energy transition will require a rapid deployment of renewable energy (RE) and electric vehicles (EVs) where other transit modes are unavailable. EV batteries could complement RE generation by providing short-term grid services. However, estimating the market opportunity requires an understanding of many socio-technical parameters and constraints. We quantify the global EV battery capacity available for grid storage using an integrated model incorporating future EV battery deployment, battery degradation, and market participation. We include both in-use and end-of-vehicle-life use phases and find a technical capacity of 32–62 terawatt-hours by 2050. Low participation rates of 12%–43% are needed to provide short-term grid storage demand globally. Participation rates fall below 10% if half of EV batteries at end-of-vehicle-life are used as stationary storage. Short-term grid storage demand could be met as early as 2030 across most regions. Our estimates are generally conservative and offer a lower bound of future opportunities.

Suggested Citation

  • Chengjian Xu & Paul Behrens & Paul Gasper & Kandler Smith & Mingming Hu & Arnold Tukker & Bernhard Steubing, 2023. "Electric vehicle batteries alone could satisfy short-term grid storage demand by as early as 2030," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-022-35393-0
    DOI: 10.1038/s41467-022-35393-0
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    2. Liu, Chenghao & Deng, Zhongwei & Zhang, Xiaohong & Bao, Huanhuan & Cheng, Duanqian, 2024. "Battery state of health estimation across electrochemistry and working conditions based on domain adaptation," Energy, Elsevier, vol. 297(C).

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