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Integrating Bidirectionally Chargeable Electric Vehicles into the Electricity Markets

Author

Listed:
  • Timo Kern

    (Forschungsgesellschaft für Energiewirtschaft mbH (FfE), 80995 Munich, Germany
    Department of Electrical and Computer Engineering, Technical University of Munich (TUM), Arcisstraße 21, 80333 München, Germany)

  • Patrick Dossow

    (Forschungsgesellschaft für Energiewirtschaft mbH (FfE), 80995 Munich, Germany)

  • Serafin von Roon

    (Forschungsgesellschaft für Energiewirtschaft mbH (FfE), 80995 Munich, Germany)

Abstract

Replacing traditional internal combustion engine vehicles with electric vehicles (EVs) proves to be challenging for the transport sector, particularly due to the higher initial investment. As EVs could be more profitable by participating in the electricity markets, the aim of this paper is to investigate revenue potentials when marketing bidirectionally chargeable electric vehicles in the spot market. To simulate a realistic marketing behavior of electric vehicles, a mixed integer linear, rolling horizon optimization model is formulated considering real trading times in the day-ahead and intraday market. Results suggest that revenue potentials are strongly dependent on the EV pool, the user behavior and the regulatory framework. Modeled potential revenues of EVs of current average size marketed with 2019 German day-ahead prices are found to be at around 200 €/EV/a, which is comparable to other findings in literature, and go up to 500 €/EV/a for consecutive trading in German day-ahead and intraday markets. For future EVs with larger batteries and higher efficiencies, potential revenues for current market prices can reach up to 1300 €/EV/a. This study finds that revenues differ widely for different European countries and future perspectives. The identified revenues give EV owners a clear incentive to participate in vehicle-to-grid use cases, thereby increasing much needed flexibility for the energy system of the future.

Suggested Citation

  • Timo Kern & Patrick Dossow & Serafin von Roon, 2020. "Integrating Bidirectionally Chargeable Electric Vehicles into the Electricity Markets," Energies, MDPI, vol. 13(21), pages 1-30, November.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:21:p:5812-:d:441110
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    References listed on IDEAS

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    6. Patrick Dossow & Maximilian Hampel, 2023. "Synergies of Electric Vehicle Multi-Use: Analyzing the Implementation Effort for Use Case Combinations in Smart E-Mobility," Energies, MDPI, vol. 16(5), pages 1-35, March.
    7. Qin Chen & Komla Agbenyo Folly, 2022. "Application of Artificial Intelligence for EV Charging and Discharging Scheduling and Dynamic Pricing: A Review," Energies, MDPI, vol. 16(1), pages 1-26, December.
    8. Alexander J. Bogensperger & Yann Fabel & Joachim Ferstl, 2022. "Accelerating Energy-Economic Simulation Models via Machine Learning-Based Emulation and Time Series Aggregation," Energies, MDPI, vol. 15(3), pages 1-42, February.
    9. Ioan-Sorin Sorlei & Nicu Bizon & Phatiphat Thounthong & Mihai Varlam & Elena Carcadea & Mihai Culcer & Mariana Iliescu & Mircea Raceanu, 2021. "Fuel Cell Electric Vehicles—A Brief Review of Current Topologies and Energy Management Strategies," Energies, MDPI, vol. 14(1), pages 1-29, January.

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