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Impact of mass-scale deployment of electric vehicles and benefits of smart charging across all European countries

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  • Mangipinto, Andrea
  • Lombardi, Francesco
  • Sanvito, Francesco Davide
  • Pavičević, Matija
  • Quoilin, Sylvain
  • Colombo, Emanuela

Abstract

The mass-scale integration of electric vehicles into the power system is a key pillar of the European energy transition agenda. Yet, the extent to which such integration would represent a burden for the power system of each member country is still an unanswered question. This is mainly due to a lack of accurate and context-specific representations of aggregate mobility and charging patterns for large electric vehicle fleets. Here, we develop and validate against empirical data an open-source model that simulates such patterns at high (1-min) temporal resolution, based on easy-to-gather, openly accessible data. We hence apply the model – which we name RAMP-mobility – to 28 European countries, showing for the first time the existence of marked differences in mobility and charging patterns across those, due to a combination of weather and socio-economic factors. We hence quantify the impact that fully-electric car fleets would have on the demand to be met by each country’s power system: an uncontrolled deployment of electric vehicles would increase peak demand in the range 35–51%, whilst a plausible share of adoption of smart charging strategies could limit the increase to 30–41%. On the contrary, plausible technology (battery density) and infrastructure (charging power) developments would not provide substantial benefits. Efforts for electric vehicles integration should hence primarily focus on mechanisms to support smart vehicle-to-grid interaction. The approach is applicable generally beyond Europe and can provide policy makers with quantitatively reliable insights about electric vehicles impact on the power system.

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  • Mangipinto, Andrea & Lombardi, Francesco & Sanvito, Francesco Davide & Pavičević, Matija & Quoilin, Sylvain & Colombo, Emanuela, 2022. "Impact of mass-scale deployment of electric vehicles and benefits of smart charging across all European countries," Applied Energy, Elsevier, vol. 312(C).
  • Handle: RePEc:eee:appene:v:312:y:2022:i:c:s0306261922001416
    DOI: 10.1016/j.apenergy.2022.118676
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    as
    1. Gaete-Morales, Carlos & Kramer, Hendrik & Schill, Wolf-Peter, 2021. "An open tool for creating battery-electric vehicle time series from empirical data, emobpy," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 8.
    2. Matteo Muratori, 2018. "Impact of uncoordinated plug-in electric vehicle charging on residential power demand," Nature Energy, Nature, vol. 3(3), pages 193-201, March.
    3. Staffell, Iain & Pfenninger, Stefan, 2018. "The increasing impact of weather on electricity supply and demand," Energy, Elsevier, vol. 145(C), pages 65-78.
    4. Jaehyung An & Fe Amor Parel Gudmundsson & Natalia Sokolinskaya & Sergey Prosekov & Artur Meynkhard & Au?unn Arn rsson & Lernui Simonyan, 2020. "Efficiency of Renewable Energy Plants in Russia," International Journal of Energy Economics and Policy, Econjournals, vol. 10(2), pages 81-88.
    5. Fischer, David & Harbrecht, Alexander & Surmann, Arne & McKenna, Russell, 2019. "Electric vehicles’ impacts on residential electric local profiles – A stochastic modelling approach considering socio-economic, behavioural and spatial factors," Applied Energy, Elsevier, vol. 233, pages 644-658.
    6. Heuberger, Clara F. & Bains, Praveen K. & Mac Dowell, Niall, 2020. "The EV-olution of the power system: A spatio-temporal optimisation model to investigate the impact of electric vehicle deployment," Applied Energy, Elsevier, vol. 257(C).
    7. Niklas Wulff & Felix Steck & Hans Christian Gils & Carsten Hoyer-Klick & Bent van den Adel & John E. Anderson, 2020. "Comparing Power-System and User-Oriented Battery Electric Vehicle Charging Representation and Its Implications on Energy System Modeling," Energies, MDPI, vol. 13(5), pages 1-41, March.
    8. Harris, Chioke B. & Webber, Michael E., 2014. "An empirically-validated methodology to simulate electricity demand for electric vehicle charging," Applied Energy, Elsevier, vol. 126(C), pages 172-181.
    9. Iversen, Emil B. & Morales, Juan M. & Madsen, Henrik, 2014. "Optimal charging of an electric vehicle using a Markov decision process," Applied Energy, Elsevier, vol. 123(C), pages 1-12.
    10. Uddin, Kotub & Dubarry, Matthieu & Glick, Mark B., 2018. "The viability of vehicle-to-grid operations from a battery technology and policy perspective," Energy Policy, Elsevier, vol. 113(C), pages 342-347.
    11. ., 2020. "The power of energy cultures," Chapters, in: Energy Cultures, chapter 6, pages 106-121, Edward Elgar Publishing.
    12. ., 2020. "Justice and equity in the energy system," Chapters, in: Energy Cultures, chapter 7, pages 122-144, Edward Elgar Publishing.
    13. David Popp, 2020. "Promoting Clean Energy Innovation," ifo DICE Report, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 17(04), pages 30-35, January.
    14. Bao, Helen X.H. & Li, Steven Haotong, 2020. "Housing wealth and residential energy consumption," Energy Policy, Elsevier, vol. 143(C).
    15. ., 2020. "National energy infrastructure," Chapters, in: The Infrastructured State, chapter 4, pages 82-105, Edward Elgar Publishing.
    16. Kwangman An & Hyehyun Kang & Youngkuk An & Jinil Park & Jonghwa Lee, 2020. "Methodology of Excavator System Energy Flow-Down," Energies, MDPI, vol. 13(4), pages 1-19, February.
    17. Huang, Bing & Meijssen, Aart Gerard & Annema, Jan Anne & Lukszo, Zofia, 2021. "Are electric vehicle drivers willing to participate in vehicle-to-grid contracts? A context-dependent stated choice experiment," Energy Policy, Elsevier, vol. 156(C).
    18. Pavičević, Matija & Mangipinto, Andrea & Nijs, Wouter & Lombardi, Francesco & Kavvadias, Konstantinos & Jiménez Navarro, Juan Pablo & Colombo, Emanuela & Quoilin, Sylvain, 2020. "The potential of sector coupling in future European energy systems: Soft linking between the Dispa-SET and JRC-EU-TIMES models," Applied Energy, Elsevier, vol. 267(C).
    19. Lombardi, Francesco & Balderrama, Sergio & Quoilin, Sylvain & Colombo, Emanuela, 2019. "Generating high-resolution multi-energy load profiles for remote areas with an open-source stochastic model," Energy, Elsevier, vol. 177(C), pages 433-444.
    20. ., 2020. "Combustion of energy cultures in Eastern Europe," Chapters, in: Energy Cultures, chapter 2, pages 34-56, Edward Elgar Publishing.
    21. Helmus, J.R. & Spoelstra, J.C. & Refa, N. & Lees, M. & van den Hoed, R., 2018. "Assessment of public charging infrastructure push and pull rollout strategies: The case of the Netherlands," Energy Policy, Elsevier, vol. 121(C), pages 35-47.
    22. Gonzalez Sanchez, Rocio & Seliger, Roman & Fahl, Fernando & De Felice, Luca & Ouarda, Taha B.M.J. & Farinosi, Fabio, 2020. "Freshwater use of the energy sector in Africa," Applied Energy, Elsevier, vol. 270(C).
    23. Pagani, M. & Korosec, W. & Chokani, N. & Abhari, R.S., 2019. "User behaviour and electric vehicle charging infrastructure: An agent-based model assessment," Applied Energy, Elsevier, vol. 254(C).
    24. Pfenninger, Stefan & DeCarolis, Joseph & Hirth, Lion & Quoilin, Sylvain & Staffell, Iain, 2017. "The importance of open data and software: Is energy research lagging behind?," Energy Policy, Elsevier, vol. 101(C), pages 211-215.
    25. Michel Noussan & Francesco Neirotti, 2020. "Cross-Country Comparison of Hourly Electricity Mixes for EV Charging Profiles," Energies, MDPI, vol. 13(10), pages 1-14, May.
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