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Charging infrastructure access and operation to reduce the grid impacts of deep electric vehicle adoption

Author

Listed:
  • Siobhan Powell

    (Stanford University
    ETH Zurich)

  • Gustavo Vianna Cezar

    (SLAC National Accelerator Laboratory)

  • Liang Min

    (Stanford University)

  • Inês M. L. Azevedo

    (Stanford University
    Stanford University
    Stanford University)

  • Ram Rajagopal

    (Stanford University
    Stanford University
    Stanford University)

Abstract

Electric vehicles will contribute to emissions reductions in the United States, but their charging may challenge electricity grid operations. We present a data-driven, realistic model of charging demand that captures the diverse charging behaviours of future adopters in the US Western Interconnection. We study charging control and infrastructure build-out as critical factors shaping charging load and evaluate grid impact under rapid electric vehicle adoption with a detailed economic dispatch model of 2035 generation. We find that peak net electricity demand increases by up to 25% with forecast adoption and by 50% in a stress test with full electrification. Locally optimized controls and high home charging can strain the grid. Shifting instead to uncontrolled, daytime charging can reduce storage requirements, excess non-fossil fuel generation, ramping and emissions. Our results urge policymakers to reflect generation-level impacts in utility rates and deploy charging infrastructure that promotes a shift from home to daytime charging.

Suggested Citation

  • Siobhan Powell & Gustavo Vianna Cezar & Liang Min & Inês M. L. Azevedo & Ram Rajagopal, 2022. "Charging infrastructure access and operation to reduce the grid impacts of deep electric vehicle adoption," Nature Energy, Nature, vol. 7(10), pages 932-945, October.
    • Handle: RePEc:nat:natene:v:7:y:2022:i:10:d:10.1038_s41560-022-01105-7
    DOI: 10.1038/s41560-022-01105-7
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    References listed on IDEAS

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