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Wake asymmetry of yaw state wind turbines induced by interference with wind towers

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  • Shibuya, Koichiro
  • Uchida, Takanori

Abstract

Wind turbine wakes are known to cause significant reductions in power generation and increased load on downwind wind turbines. Therefore, controlling wind turbine wakes is crucial, and yaw steering is considered one of the most effective methods of doing so. In this study, wind tunnel experiments using a wind turbine model and Large-eddy simulations (LES) were conducted to gain a better understanding of the wake of a yawed wind turbine. The results showed a clear difference in the horizontal distribution of wake velocity at hub height for positive and negative yaw angles, as well as both lateral and vertical wake deflections. Further investigation revealed that wind towers have a significant effect on the wakes of yawing wind turbines. For positive yaw angles, the velocity deficit is larger above the rotor, resulting in a vertical wake shape caused by the interference between the blade wakes and detached flow from the tower. Conversely, for negative yaw angles, the velocity deficit is larger below the rotor, resulting in a horizontal wake shape. These findings will facilitate the development of more accurate wake models and control methods.

Suggested Citation

  • Shibuya, Koichiro & Uchida, Takanori, 2023. "Wake asymmetry of yaw state wind turbines induced by interference with wind towers," Energy, Elsevier, vol. 280(C).
    • Handle: RePEc:eee:energy:v:280:y:2023:i:c:s0360544223014858
    DOI: 10.1016/j.energy.2023.128091
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    References listed on IDEAS

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    1. Harsh S. Dhiman & Dipankar Deb & Vlad Muresan & Valentina E. Balas, 2019. "Wake Management in Wind Farms: An Adaptive Control Approach," Energies, MDPI, vol. 12(7), pages 1-18, April.
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    4. Guo-Wei Qian & Takeshi Ishihara, 2018. "A New Analytical Wake Model for Yawed Wind Turbines," Energies, MDPI, vol. 11(3), pages 1-24, March.
    5. Qian, Guo-Wei & Ishihara, Takeshi, 2021. "Wind farm power maximization through wake steering with a new multiple wake model for prediction of turbulence intensity," Energy, Elsevier, vol. 220(C).
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    1. Ye, Shitong & Wang, Qiang & Mu, Yanfei & Luo, Kun & Fan, Jianren, 2024. "Loads and fatigue characteristics assessment of wind farm based on dynamic wake meandering model," Renewable Energy, Elsevier, vol. 236(C).

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