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Turbulence-resolving simulations of wind turbine wakes

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  • Deskos, Georgios
  • Laizet, Sylvain
  • Piggott, Matthew D.

Abstract

Turbulence-resolving simulations of wind turbine wakes are presented using a high-order flow solver combined with both a standard and a novel dynamic implicit spectral vanishing viscosity (iSVV and dynamic iSVV) model to account for subgrid-scale (SGS) stresses. The numerical solutions are compared against wind tunnel measurements, which include mean velocity and turbulent intensity profiles, as well as integral rotor quantities such as power and thrust coefficients. For the standard (also termed static) case the magnitude of the spectral vanishing viscosity is selected via a heuristic analysis of the wake statistics, while in the case of the dynamic model the magnitude is adjusted both in space and time at each time step. The study focuses on examining the ability of the two approaches, standard (static) and dynamic, to accurately capture the wake features, both qualitatively and quantitatively. The results suggest that the static method can become over-dissipative when the magnitude of the spectral viscosity is increased, while the dynamic approach which adjusts the magnitude of dissipation locally is shown to be more appropriate for a non-homogeneous flow such that of a wind turbine wake.

Suggested Citation

  • Deskos, Georgios & Laizet, Sylvain & Piggott, Matthew D., 2019. "Turbulence-resolving simulations of wind turbine wakes," Renewable Energy, Elsevier, vol. 134(C), pages 989-1002.
    • Handle: RePEc:eee:renene:v:134:y:2019:i:c:p:989-1002
    DOI: 10.1016/j.renene.2018.11.084
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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. Pierella, Fabio & Krogstad, Per-Åge & Sætran, Lars, 2014. "Blind Test 2 calculations for two in-line model wind turbines where the downstream turbine operates at various rotational speeds," Renewable Energy, Elsevier, vol. 70(C), pages 62-77.
    4. Krogstad, Per-Åge & Eriksen, Pål Egil, 2013. "“Blind test” calculations of the performance and wake development for a model wind turbine," Renewable Energy, Elsevier, vol. 50(C), pages 325-333.
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    Cited by:

    1. Ye, Maokun & Chen, Hamn-Ching & Koop, Arjen, 2023. "High-fidelity CFD simulations for the wake characteristics of the NTNU BT1 wind turbine," Energy, Elsevier, vol. 265(C).
    2. Guo, Zijian & Liu, Tanghong & Xu, Kai & Wang, Junyan & Li, Wenhui & Chen, Zhengwei, 2020. "Parametric analysis and optimization of a simple wind turbine in high speed railway tunnels," Renewable Energy, Elsevier, vol. 161(C), pages 825-835.

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