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Friedrich-Alexander-Universität Digital Transformation: Bits to Energy Lab Nuremberg WiSo
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    1. Friedrich-Alexander-Universität
    2. Fachbereich Wirtschafts- und Sozialwissenschaften
    Friedrich-Alexander-Universität Digital Transformation: Bits to Energy Lab Nuremberg WiSo
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    3. Techno-economic analyses of energy systems and technologies
    4. Demand-response with electric vehicles: charge later, support the grid now

    Demand-response with electric vehicles: charge later, support the grid now

    In page navigation: Research_alt
    • Techno-economic analyses of energy systems and technologies
      • Demand-response with electric vehicles: charge later, support the grid now
      • Local grid vs. global emissions: electric vehicle charging
      • Quantifying the potential of electric vehicles for demand-side flexibility
      • Solar energy community design: How many members, how many prosumers, what PV system sizes?
      • Solar PV Sharing in Urban Energy Communities
    • Persuasive technologies
      • Greener or Faster? Debiasing travel time presentation in travel planning apps
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    Demand-response with electric vehicles: charge later, support the grid now

    Contact

    Prakhar Mehta

    Prakhar Mehta

    Ehemaliger Mitarbeiter

    Fachbereich Wirtschafts- und Sozialwissenschaften
    Tenure-Track-Professur für Digitale Transformation

    Nürnberg
    • E-Mail: prakhar.mehta@fau.de
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    Challenge

    The energy transition is being driven by the electrification of heating and transportation. Heat pumps and electric vehicles (EVs) increase the electricity demand, and simultaneous use of these devices by multiple households may lead to overloading the local electricity network and expensive grid upgrades may be necessary. Until the prevalence of electric vehicle smart charging, can direct communication with EVs defer charging to later times to help avoid these problems?

    Approach

    We use a real-world GPS-labelled mobility dataset with over four million trips across two years from conventional cars, eliminating early EV-adopter bias. We simulate EV charging and quantify the potential for spontaneous curtailment by deferring uncontrolled charging to a later time. Our approach requires minimal infrastructure adjustments and resembles existing incentive-based demand response techniques. The curtailment potential is quantified at different times of day, for varying battery sizes, charger powers and driver types.

    Key Results

    Results indicate that the average curtailment potential per EV is 0.02-0.72 kW, significantly lower than the charging power of 11 kW, due to low EV availability (1.20-22.85% EVs charge simultaneously, and 0.42-13.87% can postpone charging). We report standardized EV charging curtailment profiles for utility planning and regulatory support to foster new business models and demand response products. This approach may unlock EVs’ potential for demand response services at scale in a timely manner, and offer a simple reference for EV smart charging which may need more time and investment to become prevalent.

    Funding

    This research is funded by the Bavarian State Ministry of Science and the Arts, in a program coordinated by the Bavarian Research Institute for Digital Transformation (bidt).

    Team

    Prakhar Mehta, Verena Tiefenbeck, Thorsten Staake (University of Bamberg)

    Friedrich-Alexander-Universität
    Lehrstuhl für Digitale Transformation

    Lange Gasse 20
    90403 Nürnberg
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