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Real-Time Estimation Methods for the Frequency Support Function Based on a Virtual Wind Turbine

Author

Listed:
  • Bo-Hyun Woo

    (Department of Electrical Engineering, Kwangwoon University, Seoul 01897, Republic of Korea)

  • Ye-Chan Kim

    (Department of Electrical Engineering, Kwangwoon University, Seoul 01897, Republic of Korea)

  • Seung-Ho Song

    (Department of Electrical Engineering, Kwangwoon University, Seoul 01897, Republic of Korea)

Abstract

With the increasing penetration of renewable energy sources, reduced system inertia and weakened frequency regulation capability have emerged as critical issues in power systems. As a result, wind turbines are now required to provide frequency support functions. To enable accurate analysis of the operational characteristics of wind turbines equipped with such control functions, this study proposes a virtual wind turbine model that estimates the operating point of a wind turbine in real-time under the assumption that frequency support functions are not performed. The proposed model is based on a turbine state observer that estimates wind speed and the power coefficient, and subsequently estimates generator power, generator speed, and blade pitch angle across various operating modes. Simulations were conducted under conditions with fluctuating wind speed and grid frequency, including MPPT, speed control, and pitch control operating regions. The accuracy of the proposed estimation model was evaluated, and the results demonstrated low estimation errors for key variables such as generator speed, power output, pitch angle, and wind speed across all conditions. These results quantitatively validate the robustness and applicability of the proposed model.

Suggested Citation

  • Bo-Hyun Woo & Ye-Chan Kim & Seung-Ho Song, 2025. "Real-Time Estimation Methods for the Frequency Support Function Based on a Virtual Wind Turbine," Energies, MDPI, vol. 18(11), pages 1-16, May.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:11:p:2774-:d:1665106
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    References listed on IDEAS

    as
    1. Cheng, Yi & Azizipanah-Abarghooee, Rasoul & Azizi, Sadegh & Ding, Lei & Terzija, Vladimir, 2020. "Smart frequency control in low inertia energy systems based on frequency response techniques: A review," Applied Energy, Elsevier, vol. 279(C).
    2. Baolong Nguyen Phung & Yuan-Kang Wu & Manh-Hai Pham, 2024. "Novel Fuzzy Logic Controls to Enhance Dynamic Frequency Control and Pitch Angle Regulation in Variable-Speed Wind Turbines," Energies, MDPI, vol. 17(11), pages 1-26, May.
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