IDEAS home Printed from https://ideas.repec.org/p/hal/wpaper/hal-03609361.html
   My bibliography  Save this paper

The impact of Electric Vehicle fleets on the European Electricity Markets : Evidences from the German Passenger Car Fleet and Power Generation Sector

Author

Listed:
  • Maria Juliana Suarrez Foréro

    (IFPEN - IFP Energies nouvelles, IFP School, RENAULT, Chaire EEM - Chaire European Electricity Markets - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres)

  • Frédéric Lantz

    (IFPEN - IFP Energies nouvelles, IFP School)

  • Pierre Nicolas

    (RENAULT)

  • Pierre Geoffron

    (Chaire EEM - Chaire European Electricity Markets - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres)

Abstract

The rapidly increasing participation of renewable energies (REn) into the electric mix, clearly traces the trends for the decarbonization goals in the European Union. Under the priority sale conditions established by governments, the commercialization of REn plays an important role in the consolidation of market prices, which are on a decreasing trend with large fluctuations that reduce the profit in the power sector and therefore, the interest of potential investors. The incorporation of small power capacities, available with a considerable fleet of electric vehicles (EV) disposed to support the bulk power system through an intelligent, and possibly bidirectional recharging system (the vehicle grid integration VGI), could have a positive impact on the electricity market as well as in CO2 emissions. In this context, our purpose is to simulate the impact of a large development of EV on the electricity market and the economic surplus of the power sector. Through a VGI tool that includes an algorithm of smart charging, we simulate the behavior of a fleet composed by some millions of EV as follows: a decentralized VGI algorithm of smart charging included in each EV estimates the energy consumption in time of the EV fleet. For a specific number of EV, we simulate the aggregated charge on the power grid, and anticipate the total expected load curve for one day. We use the estimated load curve as input in an electricity market model for calculating the producer's surplus over one year. We show that the increasing EV fleet significantly decreases the fluctuation of the residual electricity demand as well as the electricity price. Consequently, this has a positive impact on the surplus of the sector.

Suggested Citation

  • Maria Juliana Suarrez Foréro & Frédéric Lantz & Pierre Nicolas & Pierre Geoffron, 2022. "The impact of Electric Vehicle fleets on the European Electricity Markets : Evidences from the German Passenger Car Fleet and Power Generation Sector," Working Papers hal-03609361, HAL.
    • Handle: RePEc:hal:wpaper:hal-03609361
    Note: View the original document on HAL open archive server: https://ifp.hal.science/hal-03609361
    as

    Download full text from publisher

    File URL: https://ifp.hal.science/hal-03609361/document
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Richardson, David B., 2013. "Electric vehicles and the electric grid: A review of modeling approaches, Impacts, and renewable energy integration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 19(C), pages 247-254.
    2. Marc Petit & Yannick Perez, 2013. "Vehicle-to-grid in France: what revenues for participation in frequency control," Post-Print hal-01660399, HAL.
    3. Jan Smolen & Branislav Dudic, 2017. "The Role of Residual Demand in Electricity Price Analysis and Forecasting: Case of Czech Electricity Market," International Journal of Energy Economics and Policy, Econjournals, vol. 7(5), pages 152-158.
    4. Jeannie Oliver, Benjamin Sovacool, 2017. "The Energy Trilemma and the Smart Grid: Implications Beyond the United States," Asia and the Pacific Policy Studies 201705, Crawford School of Public Policy, The Australian National University.
    5. Nicolosi, Marco, 2010. "Wind power integration and power system flexibility-An empirical analysis of extreme events in Germany under the new negative price regime," Energy Policy, Elsevier, vol. 38(11), pages 7257-7268, November.
    6. Do, Linh Phuong Catherine & Lyócsa, Štefan & Molnár, Peter, 2021. "Residual electricity demand: An empirical investigation," Applied Energy, Elsevier, vol. 283(C).
    7. Andreas Wagner, 2014. "Residual Demand Modeling and Application to Electricity Pricing," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    8. Noel, Lance & Papu Carrone, Andrea & Jensen, Anders Fjendbo & Zarazua de Rubens, Gerardo & Kester, Johannes & Sovacool, Benjamin K., 2019. "Willingness to pay for electric vehicles and vehicle-to-grid applications: A Nordic choice experiment," Energy Economics, Elsevier, vol. 78(C), pages 525-534.
    9. Li, Wenbo & Long, Ruyin & Chen, Hong & Geng, Jichao, 2017. "A review of factors influencing consumer intentions to adopt battery electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 318-328.
    10. Percebois, Jacques & Pommeret, Stanislas, 2019. "Storage cost induced by a large substitution of nuclear by intermittent renewable energies: The French case," Energy Policy, Elsevier, vol. 135(C).
    11. Jeannie Oliver & Benjamin Sovacool, 2017. "The Energy Trilemma and the Smart Grid: Implications Beyond the United States," Asia and the Pacific Policy Studies, Wiley Blackwell, vol. 4(1), pages 70-84, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Maria Juliana Suarrez Foréro & Frédéric Lantz & Pierre Nicolas & Patrice Geoffron, 2022. "The Impact of Electric Vehicle Fleets on the European Electricity Markets: Evidences from the German Passenger Car Fleet and Power Generation Sector," Working Papers hal-03898558, HAL.
    2. Alabi, Oluwafisayo & Turner, Karen & Figus, Gioele & Katris, Antonios & Calvillo, Christian, 2020. "Can spending to upgrade electricity networks to support electric vehicles (EVs) roll-outs unlock value in the wider economy?," Energy Policy, Elsevier, vol. 138(C).
    3. Oryani, Bahareh & Koo, Yoonmo & Shafiee, Afsaneh & Rezania, Shahabaldin & Jung, Jiyeon & Choi, Hyunhong & Khan, Muhammad Kamran, 2022. "Heterogeneous preferences for EVs: Evidence from Iran," Renewable Energy, Elsevier, vol. 181(C), pages 675-691.
    4. Lin, Boqiang & Shi, Lei, 2022. "Do environmental quality and policy changes affect the evolution of consumers’ intentions to buy new energy vehicles," Applied Energy, Elsevier, vol. 310(C).
    5. Boßmann, Tobias & Eser, Eike Johannes, 2016. "Model-based assessment of demand-response measures—A comprehensive literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1637-1656.
    6. Do, Linh Phuong Catherine & Lyócsa, Štefan & Molnár, Peter, 2021. "Residual electricity demand: An empirical investigation," Applied Energy, Elsevier, vol. 283(C).
    7. Zhang, Qi & Liu, Jiangfeng & Yang, Kexin & Liu, Boyu & Wang, Ge, 2022. "Market adoption simulation of electric vehicle based on social network model considering nudge policies," Energy, Elsevier, vol. 259(C).
    8. Aritra Ghosh, 2020. "Possibilities and Challenges for the Inclusion of the Electric Vehicle (EV) to Reduce the Carbon Footprint in the Transport Sector: A Review," Energies, MDPI, vol. 13(10), pages 1-22, May.
    9. Huang, Youlin & Qian, Lixian, 2021. "Consumer adoption of electric vehicles in alternative business models," Energy Policy, Elsevier, vol. 155(C).
    10. Chaouachi, Aymen & Bompard, Ettore & Fulli, Gianluca & Masera, Marcelo & De Gennaro, Michele & Paffumi, Elena, 2016. "Assessment framework for EV and PV synergies in emerging distribution systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 719-728.
    11. Gerbaulet, Clemens & von Hirschhausen, Christian & Kemfert, Claudia & Lorenz, Casimir & Oei, Pao-Yu, 2019. "European electricity sector decarbonization under different levels of foresight," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 141, pages 973-987.
    12. Maria Taljegard & Lisa Göransson & Mikael Odenberger & Filip Johnsson, 2021. "To Represent Electric Vehicles in Electricity Systems Modelling—Aggregated Vehicle Representation vs. Individual Driving Profiles," Energies, MDPI, vol. 14(3), pages 1-25, January.
    13. Funcke, Simon & Bauknecht, Dierk, 2016. "Typology of centralised and decentralised visions for electricity infrastructure," Utilities Policy, Elsevier, vol. 40(C), pages 67-74.
    14. Sandrine Mathy & Patrick Criqui & Katharina Knoop & Manfred Fischedick & Sascha Samadi, 2016. "Uncertainty management and the dynamic adjustment of deep decarbonization pathways," Climate Policy, Taylor & Francis Journals, vol. 16(sup1), pages 47-62, June.
    15. Blarke, Morten B., 2012. "Towards an intermittency-friendly energy system: Comparing electric boilers and heat pumps in distributed cogeneration," Applied Energy, Elsevier, vol. 91(1), pages 349-365.
    16. Natascia Andrenacci & Roberto Ragona & Antonino Genovese, 2020. "Evaluation of the Instantaneous Power Demand of an Electric Charging Station in an Urban Scenario," Energies, MDPI, vol. 13(11), pages 1-19, May.
    17. Nicolosi, Marco, 2011. "The impact of RES-E policy setting on integration effects - A detailed analysis of capacity expansion and dispatch results," MPRA Paper 31835, University Library of Munich, Germany.
    18. Audoly, Richard & Vogt-Schilb, Adrien & Guivarch, Céline & Pfeiffer, Alexander, 2018. "Pathways toward zero-carbon electricity required for climate stabilization," Applied Energy, Elsevier, vol. 225(C), pages 884-901.
    19. Jean-Michel Clairand & Paulo Guerra-Terán & Xavier Serrano-Guerrero & Mario González-Rodríguez & Guillermo Escrivá-Escrivá, 2019. "Electric Vehicles for Public Transportation in Power Systems: A Review of Methodologies," Energies, MDPI, vol. 12(16), pages 1-22, August.
    20. Tuğba Yeğin & Muhammad Ikram, 2022. "Analysis of Consumers’ Electric Vehicle Purchase Intentions: An Expansion of the Theory of Planned Behavior," Sustainability, MDPI, vol. 14(19), pages 1-27, September.

    More about this item

    Keywords

    Energy transition; Electricity markets; Merit order effect; Vehicle grid integration.;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hal:wpaper:hal-03609361. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.