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Improvements to and Experimental Validation of PI Controllers Using a Reference Bias Control Algorithm for Wind Turbines

Author

Listed:
  • Taesu Jeon

    (Department of Integrated Energy & Infra System, Kangwon National University, Chuncheon-si 24341, Gangwon, Korea)

  • Dongmyoung Kim

    (Department of Integrated Energy & Infra System, Kangwon National University, Chuncheon-si 24341, Gangwon, Korea)

  • Insu Paek

    (Department of Integrated Energy & Infra System, Kangwon National University, Chuncheon-si 24341, Gangwon, Korea
    Department of Mechatronics Engineering, Kangwon National University, Chuncheon-si 24341, Gangwon, Korea)

Abstract

In this study, a reference bias control (RBC) algorithm for variable speed and variable pitch wind turbines was designed and validated. To improve the performance of conventional PI control algorithms, the RBC algorithm applies biased references to power and pitch angle to the pitch and the torque control loops, respectively. To validate the control performance of the improved RBC algorithm, hardware in the loop simulator (HILS) was conducted using a commercial programmable logic controller (PLC). The performance of a conventional PI control algorithm and the proposed RBC algorithm were compared for the target wind turbine model in terms of both the transition region and the rated power region. In the transition region, the proposed RBC algorithm improved the sudden dips in the generator torque and power, which often occur when using a control algorithm with a switching logic. As a result, the damage equivalent load (DEL) of the main shaft was reduced by 15%. In the rated power region, the rotor speed deviation was reduced by 22% and the power deviation was reduced by 21%. To experimentally validate the control performance and applicability of the RBC algorithm, wind tunnel testing using a wind turbine scaled model was additionally performed. Similarly to the HILS testing result, it was confirmed that the DEL of the main shaft and fluctuation of the rotor speed and power decreased with the proposed RBC algorithm.

Suggested Citation

  • Taesu Jeon & Dongmyoung Kim & Insu Paek, 2022. "Improvements to and Experimental Validation of PI Controllers Using a Reference Bias Control Algorithm for Wind Turbines," Energies, MDPI, vol. 15(21), pages 1-18, November.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:21:p:8298-:d:965197
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    References listed on IDEAS

    as
    1. Taesu Jeon & Insu Paek, 2021. "Design and Verification of the LQR Controller Based on Fuzzy Logic for Large Wind Turbine," Energies, MDPI, vol. 14(1), pages 1-17, January.
    2. Taesu Jeon & Dongmyoung Kim & Yuan Song & Insu Paek, 2021. "Design and Validation of Demanded Power Point Tracking Control Algorithm for MIMO Controllers in Wind Turbines," Energies, MDPI, vol. 14(18), pages 1-18, September.
    3. Kwansu Kim & Hyun-Gyu Kim & Yuan Song & Insu Paek, 2019. "Design and Simulation of an LQR-PI Control Algorithm for Medium Wind Turbine," Energies, MDPI, vol. 12(12), pages 1-18, June.
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    Cited by:

    1. Donggeun Jeong & Taesu Jeon & Insu Paek & Deokjin Lim, 2023. "Development and Validation of Control Algorithm for Variable Speed Fixed Pitch Small Wind Turbine," Energies, MDPI, vol. 16(4), pages 1-18, February.

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