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Interaction of Wind Turbine Wakes under Various Atmospheric Conditions

Author

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  • Sang Lee

    (Department of Mechanical Engineering, University of New Mexico, Albuquerque, NM 87131, USA)

  • Peter Vorobieff

    (Department of Mechanical Engineering, University of New Mexico, Albuquerque, NM 87131, USA)

  • Svetlana Poroseva

    (Department of Mechanical Engineering, University of New Mexico, Albuquerque, NM 87131, USA)

Abstract

We present a numerical study of two utility-scale 5-MW turbines separated by seven rotor diameters. The effects of the atmospheric boundary layer flow on the turbine performance were assessed using large-eddy simulations. We found that the surface roughness and the atmospheric stability states had a profound effect on the wake diffusion and the Reynolds stresses. In the upstream turbine case, high surface roughness increased the wind shear, accelerating the decay of the wake deficit and increasing the Reynolds stresses. Similarly, atmospheric instabilities significantly expedited the wake decay and the Reynolds stress increase due to updrafts of the thermal plumes. The turbulence from the upstream boundary layer flow combined with the turbine wake yielded higher Reynolds stresses for the downwind turbine, especially in the streamwise component. For the downstream turbine, diffusion of the wake deficits and the sharp peaks in the Reynolds stresses showed faster decay than the upwind case due to higher levels of turbulence. This provides a physical explanation for how turbine arrays or wind farms can operate more efficiently under unstable atmospheric conditions, as it is based on measurements collected in the field.

Suggested Citation

  • Sang Lee & Peter Vorobieff & Svetlana Poroseva, 2018. "Interaction of Wind Turbine Wakes under Various Atmospheric Conditions," Energies, MDPI, vol. 11(6), pages 1-15, June.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:6:p:1442-:d:150534
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    References listed on IDEAS

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    1. Sarlak, H. & Meneveau, C. & Sørensen, J.N., 2015. "Role of subgrid-scale modeling in large eddy simulation of wind turbine wake interactions," Renewable Energy, Elsevier, vol. 77(C), pages 386-399.
    2. Wu, Yu-Ting & Porté-Agel, Fernando, 2015. "Modeling turbine wakes and power losses within a wind farm using LES: An application to the Horns Rev offshore wind farm," Renewable Energy, Elsevier, vol. 75(C), pages 945-955.
    3. Kumar, Yogesh & Ringenberg, Jordan & Depuru, Soma Shekara & Devabhaktuni, Vijay K. & Lee, Jin Woo & Nikolaidis, Efstratios & Andersen, Brett & Afjeh, Abdollah, 2016. "Wind energy: Trends and enabling technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 209-224.
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    Cited by:

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    2. Huanqiang, Zhang & Xiaoxia, Gao & Hongkun, Lu & Qiansheng, Zhao & Xiaoxun, Zhu & Yu, Wang & Fei, Zhao, 2024. "Investigation of a new 3D wake model of offshore floating wind turbines subjected to the coupling effects of wind and wave," Applied Energy, Elsevier, vol. 365(C).
    3. Zhenzhou Shao & Ying Wu & Li Li & Shuang Han & Yongqian Liu, 2019. "Multiple Wind Turbine Wakes Modeling Considering the Faster Wake Recovery in Overlapped Wakes," Energies, MDPI, vol. 12(4), pages 1-14, February.

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