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Dynamic wake modulation induced by utility-scale wind turbine operation

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  • Abraham, Aliza
  • Hong, Jiarong

Abstract

Understanding wind turbine wake mixing and recovery is critical for improving the power generation and structural stability of downwind turbines in a wind farm. In the field, where incoming flow and turbine operation are constantly changing, the rate of wake recovery can be significantly influenced by dynamic wake modulation, which has not yet been explored. Here we present the first investigation of dynamic wake modulation in the near wake of an operational utility-scale wind turbine, and quantify its relationship with changing conditions. This experimental investigation is enabled using novel super-large-scale flow visualization with natural snowfall, providing unprecedented spatiotemporal resolution to resolve instantaneous changes of the wake envelope in the field. These measurements reveal the significant influence of dynamic wake modulation, which causes an increase in flux across the wake boundary of 11% on average, on wake recovery, providing insights into necessary modifications to traditional wake and farm models. Further, our study uncovers the direct connection between dynamic wake modulation and operational parameters readily available to the turbine controller such as yaw error, blade pitch, and tip speed ratio. These connections pave the way for more precise wake prediction and control algorithms under field conditions for wind farm optimization.

Suggested Citation

  • Abraham, Aliza & Hong, Jiarong, 2020. "Dynamic wake modulation induced by utility-scale wind turbine operation," Applied Energy, Elsevier, vol. 257(C).
    • Handle: RePEc:eee:appene:v:257:y:2020:i:c:s0306261919316903
    DOI: 10.1016/j.apenergy.2019.114003
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    References listed on IDEAS

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    Cited by:

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    2. Hui Liu & Peng Wang & Teyang Zhao & Zhenggang Fan & Houlin Pan, 2022. "A Group-Based Droop Control Strategy Considering Pitch Angle Protection to Deloaded Wind Farms," Energies, MDPI, vol. 15(8), pages 1-23, April.
    3. 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).
    4. Abraham, Aliza & Hong, Jiarong, 2021. "Operational-dependent wind turbine wake impact on surface momentum flux," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    5. Gao, Xiaoxia & Zhang, Shaohai & Li, Luqing & Xu, Shinai & Chen, Yao & Zhu, Xiaoxun & Sun, Haiying & Wang, Yu & Lu, Hao, 2022. "Quantification of 3D spatiotemporal inhomogeneity for wake characteristics with validations from field measurement and wind tunnel test," Energy, Elsevier, vol. 254(PA).
    6. Wen, Jiahao & Zhou, Lei & Zhang, Hongfu, 2023. "Mode interpretation of blade number effects on wake dynamics of small-scale horizontal axis wind turbine," Energy, Elsevier, vol. 263(PA).
    7. Paxis Marques João Roque & Shyama Pada Chowdhury & Zhongjie Huan, 2021. "Performance Enhancement of Proposed Namaacha Wind Farm by Minimising Losses Due to the Wake Effect: A Mozambican Case Study," Energies, MDPI, vol. 14(14), pages 1-22, July.

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