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Investigation of the near wake of a horizontal-axis wind turbine model by dynamic mode decomposition

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  • Sun, Chong
  • Tian, Tian
  • Zhu, Xiaocheng
  • Hua, Ouyang
  • Du, Zhaohui

Abstract

The wake flow of a horizontal-axis wind turbine has an important effect on the energy extraction and downstream turbulent flow. In this paper, large eddy simulation is employed to obtain the unsteady flow over a two-blade wind turbine model. The detailed geometry of the blade is resolved in the computational mesh. The wake flow is analyzed using dynamic mode decomposition (DMD). The DMD results for the wake flow in the absolute reference frame indicate that the tip vortices are the dominant unsteady flow features in the near wake. The leading energetic modes illustrate the downstream, swing and rotating motion of the tip vortices. The wake flow in a relative reference frame static to the rotor is also analyzed by DMD. The decomposition results illustrate the traveling wave structures and spatial-growth disturbances on the helical vortex filaments. The mode results suggest that the disturbances are gradually formed from the small-scale turbulences, grow rapidly on the helical vortex filament and eventually contribute to the mutual instability of the tip vortices. The breakdown of the tip vortices will lead to the wake recovery and affect the energy extraction of downstream turbines.

Suggested Citation

  • Sun, Chong & Tian, Tian & Zhu, Xiaocheng & Hua, Ouyang & Du, Zhaohui, 2021. "Investigation of the near wake of a horizontal-axis wind turbine model by dynamic mode decomposition," Energy, Elsevier, vol. 227(C).
    • Handle: RePEc:eee:energy:v:227:y:2021:i:c:s0360544221006678
    DOI: 10.1016/j.energy.2021.120418
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    References listed on IDEAS

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    Cited by:

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    2. 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).
    3. Martin Geibel & Galih Bangga, 2022. "Data Reduction and Reconstruction of Wind Turbine Wake Employing Data Driven Approaches," Energies, MDPI, vol. 15(10), pages 1-40, May.
    4. De Cillis, Giovanni & Cherubini, Stefania & Semeraro, Onofrio & Leonardi, Stefano & De Palma, Pietro, 2022. "The influence of incoming turbulence on the dynamic modes of an NREL-5MW wind turbine wake," Renewable Energy, Elsevier, vol. 183(C), pages 601-616.

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