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Large Scale Smart Charging of Electric Vehicles in Practice

Author

Listed:
  • Marisca Zweistra

    (ElaadNL, Utrechtseweg 310, building B42, 6812 AR Arnhem, The Netherlands)

  • Stan Janssen

    (ElaadNL, Utrechtseweg 310, building B42, 6812 AR Arnhem, The Netherlands)

  • Frank Geerts

    (ElaadNL, Utrechtseweg 310, building B42, 6812 AR Arnhem, The Netherlands)

Abstract

The energy system is changing due to a steady increase in electric vehicles on the demand side and local production (mostly through solar panels) on the production side. Both developments can put the energy grid under stress during certain timeframes, while there might be enough capacity on the grid most of the day. Smart charging of electric vehicles might be a solution to time dependent congestion. In this study, a smart charging strategy was developed and tested in large scale with 1000 public chargers, operated in the real word. We developed and tested protocols to temporarily limit the charger capacity based on the transformer data and the number of running sessions. Over 150,000 sessions were handled, of which almost half were influenced by the smart charging strategy applied. We found that we were able to keep within the grid limits by using these controls, without hindering the driver experience. Further improvements to the smart charging strategy can be made as soon as car manufacturers share information about the car battery such as the state of charge.

Suggested Citation

  • Marisca Zweistra & Stan Janssen & Frank Geerts, 2020. "Large Scale Smart Charging of Electric Vehicles in Practice," Energies, MDPI, vol. 13(2), pages 1-13, January.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:2:p:298-:d:306167
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    References listed on IDEAS

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    1. 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.
    2. 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.
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    Citations

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    Cited by:

    1. Gonzalez Venegas, Felipe & Petit, Marc & Perez, Yannick, 2021. "Active integration of electric vehicles into distribution grids: Barriers and frameworks for flexibility services," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    2. Simone Orcioni & Massimo Conti, 2020. "EV Smart Charging with Advance Reservation Extension to the OCPP Standard," Energies, MDPI, vol. 13(12), pages 1-21, June.
    3. Ana Carolina Kulik & Édwin Augusto Tonolo & Alberto Kisner Scortegagna & Jardel Eugênio da Silva & Jair Urbanetz Junior, 2021. "Analysis of Scenarios for the Insertion of Electric Vehicles in Conjunction with a Solar Carport in the City of Curitiba, Paraná—Brazil," Energies, MDPI, vol. 14(16), pages 1-15, August.
    4. Connor Scott & Mominul Ahsan & Alhussein Albarbar, 2021. "Machine Learning Based Vehicle to Grid Strategy for Improving the Energy Performance of Public Buildings," Sustainability, MDPI, vol. 13(7), pages 1-22, April.
    5. Ângelo Casaleiro & Rodrigo Amaro e Silva & João Serra, 2020. "Plug-in Electric Vehicles for Grid Services Provision: Proposing an Operational Characterization Procedure for V2G Systems," Energies, MDPI, vol. 13(5), pages 1-12, March.
    6. Kazmi, Hussain & Munné-Collado, Íngrid & Mehmood, Fahad & Syed, Tahir Abbas & Driesen, Johan, 2021. "Towards data-driven energy communities: A review of open-source datasets, models and tools," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    7. Wouter P. L. van Galen & Bob Walrave & Sharon A. M. Dolmans & A. Georges L. Romme, 2021. "Charging for Collaboration: Exploring the Dynamics of Temporal Fit in Interdependent Constellations for Innovation," Energies, MDPI, vol. 14(17), pages 1-23, August.
    8. Filipe Quintal & Daniel Garigali & Dino Vasconcelos & Jonathan Cavaleiro & Wilson Santos & Lucas Pereira, 2021. "Energy Monitoring in the Wild: Platform Development and Lessons Learned from a Real-World Demonstrator," Energies, MDPI, vol. 14(18), pages 1-15, September.
    9. 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.

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