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Design and Validation of Demanded Power Point Tracking Control Algorithm for MIMO Controllers in Wind Turbines

Author

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  • Taesu Jeon

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

  • Dongmyoung Kim

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

  • Yuan Song

    (Department of Advanced Mechanical Engineering, Kangwon National University, Gangwon, Chuncheon 24341, Korea)

  • Insu Paek

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

Abstract

In this study, a demanded power point tracking (DPPT) control algorithm was designed for the application of multiple-input multiple-output (MIMO) modern control algorithms. The proposed DPPT control algorithm has been newly implemented as a multiple reference trajectory method for applying an MIMO control algorithm without mode switches. Dynamic simulations and wind tunnel experiments were performed using a scaled wind turbine to validate the proposed control algorithm. The wind speeds were 4.6 and 7.3 m/s, the average wind speeds corresponding to region 2 and region 3, respectively, with a turbulence intensity of 10%. Both sets of results demonstrated satisfactory performance for tracking the power commands transmitted from the wind farm controller. Furthermore, the proposed control algorithm was compared and validated with a DPPT control algorithm proposed in previous studies, and its improved control performance and validity were confirmed.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:18:p:5818-:d:635409
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    References listed on IDEAS

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    3. Siniscalchi-Minna, Sara & Bianchi, Fernando D. & De-Prada-Gil, Mikel & Ocampo-Martinez, Carlos, 2019. "A wind farm control strategy for power reserve maximization," Renewable Energy, Elsevier, vol. 131(C), pages 37-44.
    4. Kwansu Kim & Hyunjong Kim & Hyungyu Kim & Jaehoon Son & Jungtae Kim & Jongpo Park, 2021. "Resonance Avoidance Control Algorithm for Semi-Submersible Floating Offshore Wind Turbine," Energies, MDPI, vol. 14(14), pages 1-17, July.
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    Cited by:

    1. 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.

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