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A Novel Control Strategy for the Frequency and Voltage Regulation of Distribution Grids Using Electric Vehicle Batteries

Author

Listed:
  • Mohammadshayan Latifi

    (Department of Electrical and Computer Engineering, San Diego State University, San Diego, CA 92182, USA)

  • Reza Sabzehgar

    (Department of Electrical and Computer Engineering, San Diego State University, San Diego, CA 92182, USA)

  • Poria Fajri

    (Department of Electrical and Biomedical Engineering, University of Nevada Reno, Reno, NV 89557, USA)

  • Mohammad Rasouli

    (Department of Electrical and Computer Engineering, Penn State Behrend, Erie, PA 16563, USA)

Abstract

In this study, a double-loop control strategy is proposed for power grid frequency and voltage regulation using plug-in electric vehicles (PEVs) connected to the grid through a three-level capacitor clamped inverter. The frequency and voltage regulation problem is first formulated using vector space analysis and phasor diagrams to find the boundaries and constraints in terms of the system parameters. The derived formulas are then utilized to design a double-loop controller using an exclusive phase detector control loop and a novel pulse width modulation (PWM) scheme to effectively regulate the frequency and voltage of the grid. The effectiveness and feasibility of the proposed control strategy are evaluated through simulation and experimental studies. This approach can benefit both the customers and the grid operator, as it facilitates utilizing the batteries of the connected PEVs to supply a portion or all of the active and reactive power demand, hence regulating the frequency and voltage of the grid. The extent to which active and reactive power can be supplied depends on the number of PEVs connected to the local grid.

Suggested Citation

  • Mohammadshayan Latifi & Reza Sabzehgar & Poria Fajri & Mohammad Rasouli, 2021. "A Novel Control Strategy for the Frequency and Voltage Regulation of Distribution Grids Using Electric Vehicle Batteries," Energies, MDPI, vol. 14(5), pages 1-16, March.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:5:p:1435-:d:511619
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    References listed on IDEAS

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    1. Reza Sabzehgar & Yaser M. Roshan & Poria Fajri, 2020. "Modeling and Control of a Multifunctional Three-Phase Converter for Bidirectional Power Flow in Plug-In Electric Vehicles," Energies, MDPI, vol. 13(10), pages 1-19, May.
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    Cited by:

    1. Davide Deltetto & Davide Coraci & Giuseppe Pinto & Marco Savino Piscitelli & Alfonso Capozzoli, 2021. "Exploring the Potentialities of Deep Reinforcement Learning for Incentive-Based Demand Response in a Cluster of Small Commercial Buildings," Energies, MDPI, vol. 14(10), pages 1-25, May.
    2. Oussama Ouramdane & Elhoussin Elbouchikhi & Yassine Amirat & Ehsan Sedgh Gooya, 2021. "Optimal Sizing and Energy Management of Microgrids with Vehicle-to-Grid Technology: A Critical Review and Future Trends," Energies, MDPI, vol. 14(14), pages 1-45, July.
    3. Reza Sabzehgar & Diba Zia Amirhosseini & Saeed D. Manshadi & Poria Fajri, 2021. "Stochastic Expansion Planning of Various Energy Storage Technologies in Active Power Distribution Networks," Sustainability, MDPI, vol. 13(10), pages 1-17, May.
    4. Moradi Amani, A. & Sajjadi, S.S. & Al Khafaf, N. & Song, H. & Jalili, M. & Yu, X. & Meegahapola, L. & McTaggart, P., 2023. "Technology balancing for reliable EV uptake in distribution grids: An Australian case study," Renewable Energy, Elsevier, vol. 206(C), pages 939-948.

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