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Modeling the Future California Electricity Grid and Renewable Energy Integration with Electric Vehicles

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  • Florian van Triel

    (Department of Vehicle Mechatronics, Technical University of Dresden, 01069 Dresden, Germany
    Transportation Sustainability Research Center, University of California-Berkeley, Berkeley, CA 94704, USA
    BMW AG, Petuelring 130, 80788 Munich, Germany)

  • Timothy E. Lipman

    (Transportation Sustainability Research Center, University of California-Berkeley, Berkeley, CA 94704, USA)

Abstract

This study focuses on determining the impacts and potential value of unmanaged and managed uni-directional and bi-directional charging of plug-in electric vehicles (PEVs) to integrate intermittent renewable resources in California in the year 2030. The research methodology incorporates the utilization of multiple simulation tools including V2G-SIM, SWITCH, and GridSim. SWITCH is used to predict a cost-effective generation portfolio to meet the renewable electricity goals of 60% in California by 2030. PEV charging demand is predicted by incorporating mobility behavior studies and assumptions charging infrastructure and vehicle technology improvements. Finally, the production cost model GridSim is used to quantify the impacts of managed and unmanaged vehicle-charging demand to electricity grid operations. The temporal optimization of charging sessions shows that PEVs can mitigate renewable oversupply and ramping needs substantially. The results show that 3.3 million PEVs can mitigate over-generation by ~4 terawatt hours in California—potentially saving the state up to about USD 20 billion of capital investment costs in stationary storage technologies.

Suggested Citation

  • Florian van Triel & Timothy E. Lipman, 2020. "Modeling the Future California Electricity Grid and Renewable Energy Integration with Electric Vehicles," Energies, MDPI, vol. 13(20), pages 1-20, October.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:20:p:5277-:d:426327
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    References listed on IDEAS

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    Cited by:

    1. Joseph Nyangon & Ruth Akintunde, 2024. "Principal component analysis of day‐ahead electricity price forecasting in CAISO and its implications for highly integrated renewable energy markets," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 13(1), January.
    2. Powell, Siobhan & Martin, Sonia & Rajagopal, Ram & Azevedo, Inês M.L. & de Chalendar, Jacques, 2024. "Future-proof rates for controlled electric vehicle charging: Comparing multi-year impacts of different emission factor signals," Energy Policy, Elsevier, vol. 190(C).
    3. Roberto Ruggieri & Marco Ruggeri & Giuliana Vinci & Stefano Poponi, 2021. "Electric Mobility in a Smart City: European Overview," Energies, MDPI, vol. 14(2), pages 1-29, January.
    4. Soomin Woo & Zhe Fu & Elpiniki Apostolaki-Iosifidou & Timothy E. Lipman, 2021. "Economic and Environmental Benefits for Electricity Grids from Spatiotemporal Optimization of Electric Vehicle Charging," Energies, MDPI, vol. 14(24), pages 1-22, December.
    5. Theron Smith & Joseph Garcia & Gregory Washington, 2022. "Novel PEV Charging Approaches for Extending Transformer Life," Energies, MDPI, vol. 15(12), pages 1-17, June.

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