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Estimating the Impact of Electric Vehicle Demand Response Programs in a Grid with Varying Levels of Renewable Energy Sources: Time-of-Use Tariff versus Smart Charging

Author

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  • Wooyoung Jeon

    (Department of Economics, Chonnam National University, Gwangju 61186, Korea)

  • Sangmin Cho

    (Korea Energy Economics Institute, Ulsan 44543, Korea)

  • Seungmoon Lee

    (Korea Energy Economics Institute, Ulsan 44543, Korea)

Abstract

An increase in variable renewable energy sources and soaring electricity demand at peak hours undermines the efficiency and reliability of the power supply. Conventional supply-side solutions, such as additional gas turbine plants and energy storage systems, can help mitigate these problems; however, they are not cost-effective. This study highlights the potential value of electric vehicle demand response programs by analyzing three separate scenarios: electric vehicle charging based on a time-of-use tariff, smart charging controlled by an aggregator through virtual power plant networks, and smart control with vehicle-to-grid capability. The three programs are analyzed based on the stochastic form of a power system optimization model under two hypothetical power system environments in Jeju Island, Korea: one with a low share of variable renewable energy in 2019 and the other with a high share in 2030. The results show that the cost saving realized by the electric vehicle demand response program is higher in 2030 and a smart control with vehicle-to-grid capability provides the largest cost saving. When the costs of implementing an electric vehicle demand response are considered, the difference in cost saving between the scenarios is reduced; however, the benefits are still large enough to attract customers to participate.

Suggested Citation

  • Wooyoung Jeon & Sangmin Cho & Seungmoon Lee, 2020. "Estimating the Impact of Electric Vehicle Demand Response Programs in a Grid with Varying Levels of Renewable Energy Sources: Time-of-Use Tariff versus Smart Charging," Energies, MDPI, vol. 13(17), pages 1-22, August.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:17:p:4365-:d:403403
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    References listed on IDEAS

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    4. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N., 2022. "Demand response-integrated investment and operational planning of renewable and sustainable energy systems considering forecast uncertainties: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    5. Madani, Seyyedreza & Pineau, Pierre-Olivier, 2024. "Investment in vehicle-to-grid and distributed energy resources: Distributor versus prosumer perspectives and the impact of rate structures," Utilities Policy, Elsevier, vol. 88(C).
    6. Lee, Juyong & Cho, Youngsang, 2022. "Determinants of reserve margin volatility: A new approach toward managing energy supply and demand," Energy, Elsevier, vol. 252(C).
    7. Neska, Ewa & Kowalska-Pyzalska, Anna, 2022. "Conceptual design of energy market topologies for communities and their practical applications in EU: A comparison of three case studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    8. Chila Kaewpraek & Liaqat Ali & Md. Arefin Rahman & Mohammad Shakeri & M. S. Chowdhury & M. S. Jamal & Md. Shahin Mia & Jagadeesh Pasupuleti & Le Khac Dong & Kuaanan Techato, 2021. "The Effect of Plants on the Energy Output of Green Roof Photovoltaic Systems in Tropical Climates," Sustainability, MDPI, vol. 13(8), pages 1-10, April.
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    10. Dominika Kaczorowska & Jacek Rezmer & Michal Jasinski & Tomasz Sikorski & Vishnu Suresh & Zbigniew Leonowicz & Pawel Kostyla & Jaroslaw Szymanda & Przemyslaw Janik, 2020. "A Case Study on Battery Energy Storage System in a Virtual Power Plant: Defining Charging and Discharging Characteristics," Energies, MDPI, vol. 13(24), pages 1-22, December.
    11. Nnaemeka Vincent Emodi & Scott Dwyer & Kriti Nagrath & John Alabi, 2022. "Electromobility in Australia: Tariff Design Structure and Consumer Preferences for Mobile Distributed Energy Storage," Sustainability, MDPI, vol. 14(11), pages 1-18, May.
    12. Wooyoung Jeon & Jungyoun Mo, 2023. "Estimating the Operating Reserve Demand Curve for Efficient Adoption of Renewable Sources in Korea," Energies, MDPI, vol. 16(3), pages 1-12, February.

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