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Modeling Volatility and Flexibility of Electric Vehicles’ Energy Consumption

Author

Listed:
  • Muessel, Jarusch

    (Potsdam Institute for Climate Impact Research)

  • Ruhnau, Oliver

    (E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN))

  • Madlener, Reinhard

    (E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN))

Abstract

The growing number of electric vehicles (EVs) will challenge the power system, but EVs may also have balancing effects via smart charging. Modeling EVs’ system-level impact while respecting computational constraints requires the aggregation of individual profiles. We show that studies typically rely on too few profiles to accurately model EVs’ system-level impact and that a naïve aggregation of individual profiles leads to an overestimation of the fleet’s flexibility potential. To overcome this, we introduce a scalable and accurate aggregation approach based on the idea to model deviations from an uncontrolled charging strategy as a virtual energy storage unit. We apply this to German mobility statistics and estimate an average flexibility potential of 93 GWh (6.2 kWh/EV), only 10% of the result of a naïve aggregation. We conclude that our approach allows for a more realistic representation of EVs in energy system models and may be applied to other flexible assets.

Suggested Citation

  • Muessel, Jarusch & Ruhnau, Oliver & Madlener, Reinhard, 2022. "Modeling Volatility and Flexibility of Electric Vehicles’ Energy Consumption," FCN Working Papers 17/2022, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN), revised 01 May 2023.
    • Handle: RePEc:ris:fcnwpa:2022_017
    as

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    References listed on IDEAS

    as
    1. Crampes, Claude & Trochet, Jean-Michel, 2019. "Economics of stationary electricity storage with various charge and discharge durations," TSE Working Papers 19-985, Toulouse School of Economics (TSE).
    2. Kern, Timo & Dossow, Patrick & Morlock, Elena, 2022. "Revenue opportunities by integrating combined vehicle-to-home and vehicle-to-grid applications in smart homes," Applied Energy, Elsevier, vol. 307(C).
    3. San Román, Tomás Gómez & Momber, Ilan & Abbad, Michel Rivier & Sánchez Miralles, Álvaro, 2011. "Regulatory framework and business models for charging plug-in electric vehicles: Infrastructure, agents, and commercial relationships," Energy Policy, Elsevier, vol. 39(10), pages 6360-6375, October.
    4. Schücking, Maximilian & Jochem, Patrick & Fichtner, Wolf & Wollersheim, Olaf & Stella, Kevin, 2017. "Charging strategies for economic operations of electric vehicles in commercial applications," MPRA Paper 91599, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    electric vehicles; demand-side flexibility; aggregation; representativity; After Diversity Maximum Demand; energy system modeling; virtual energy storage unit;
    All these keywords.

    JEL classification:

    • A12 - General Economics and Teaching - - General Economics - - - Relation of Economics to Other Disciplines
    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics

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