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Cross-Country Comparison of Hourly Electricity Mixes for EV Charging Profiles

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  • Michel Noussan

    (Future Energy Program, Fondazione Eni Enrico Mattei, Corso Magenta 63, 20123 Milano, Italy)

  • Francesco Neirotti

    (Department of Energy, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy)

Abstract

Electric vehicles, when coupled to electricity generation from renewable energy sources, can become a viable solution to decarbonize the transport sector. However, given the high variability of electricity mixes on a daily and seasonal basis, high-resolution profiles are needed for a precise analysis of the impacts of electric vehicles in terms of greenhouse gases emissions. This paper presents a comparison of different charging profiles evaluated on 10 European countries over four years, to highlight the effects of national electricity mixes and of the type of charging location on the specific emissions of EVs charging. This study, based on three archetypal charging profiles, provide a quantification of the potential influence of different charging strategies on the average emission factor of the electricity supplied to electric vehicles. The results show that the variability related to charging profiles is generally limited, with an average variation range of 6% for any given country and year, while in several countries the variability from one year to another is much larger, with an average range of 18% for any given country and charging profile.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:10:p:2527-:d:358962
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    References listed on IDEAS

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    Cited by:

    1. Michel Noussan & Edoardo Campisi & Matteo Jarre, 2022. "Carbon Intensity of Passenger Transport Modes: A Review of Emission Factors, Their Variability and the Main Drivers," Sustainability, MDPI, vol. 14(17), pages 1-16, August.
    2. Martins, H. & Henriques, C.O. & Figueira, J.R. & Silva, C.S. & Costa, A.S., 2023. "Assessing policy interventions to stimulate the transition of electric vehicle technology in the European Union," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    3. Michel Noussan & Matteo Jarre, 2021. "Assessing Commuting Energy and Emissions Savings through Remote Working and Carpooling: Lessons from an Italian Region," Energies, MDPI, vol. 14(21), pages 1-19, November.
    4. 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).
    5. Ahmad Almaghrebi & Fares Aljuheshi & Mostafa Rafaie & Kevin James & Mahmoud Alahmad, 2020. "Data-Driven Charging Demand Prediction at Public Charging Stations Using Supervised Machine Learning Regression Methods," Energies, MDPI, vol. 13(16), pages 1-21, August.
    6. Lukas Lanz & Bessie Noll & Tobias S. Schmidt & Bjarne Steffen, 2022. "Comparing the levelized cost of electric vehicle charging options in Europe," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    7. Benedetto Nastasi & Massimiliano Manfren & Michel Noussan, 2021. "Open Data and Models for Energy and Environment," Energies, MDPI, vol. 14(15), pages 1-2, July.
    8. Pei Huang & Xingxing Zhang & Benedetta Copertaro & Puneet Kumar Saini & Da Yan & Yi Wu & Xiangjie Chen, 2020. "A Technical Review of Modeling Techniques for Urban Solar Mobility: Solar to Buildings, Vehicles, and Storage (S2BVS)," Sustainability, MDPI, vol. 12(17), pages 1-37, August.

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