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Role of subgrid-scale modeling in large eddy simulation of wind turbine wake interactions

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  • Sarlak, H.
  • Meneveau, C.
  • Sørensen, J.N.

Abstract

A series of simulations are carried out to evaluate specific features of the Large Eddy Simulation (LES) technique in wind turbine wake interactions. We aim to model wake interactions of two aligned model rotors. The effects of the rotor resolution, actuator line force filter size, and Reynolds number are investigated at certain tip speed ratios. The numerical results are validated against wind tunnel measurements in terms of the mean velocity, turbulence intensity and the power and thrust coefficients. Special emphasis is placed on the role played by subgrid scale (SGS) models in affecting the flow structures and turbine loading, as this has been studied less in prior investigations. It is found that, compared with the effects of rotor resolution and force kernel size, the SGS models have only a minor impact on the wake and predicted power performance. These observations confirm the usual expectations in the field of LES about insensitivity of wake-dominated flows to SGS modeling. However, the observed insensitivity of the near-rotor tip vortices, the thin shear layer structures, and their respective instability phenomena to SGS models are surprising and encouraging as far as accuracy levels to be expected from LES results for wind energy applications, are concerned.

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  • 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.
  • Handle: RePEc:eee:renene:v:77:y:2015:i:c:p:386-399
    DOI: 10.1016/j.renene.2014.12.036
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    1. Lignarolo, L.E.M. & Ragni, D. & Krishnaswami, C. & Chen, Q. & Simão Ferreira, C.J. & van Bussel, G.J.W., 2014. "Experimental analysis of the wake of a horizontal-axis wind-turbine model," Renewable Energy, Elsevier, vol. 70(C), pages 31-46.
    2. 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.
    3. Bastankhah, Majid & Porté-Agel, Fernando, 2014. "A new analytical model for wind-turbine wakes," Renewable Energy, Elsevier, vol. 70(C), pages 116-123.
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    8. Meng, Hang & Lien, Fue-Sang & Li, Li, 2018. "Elastic actuator line modelling for wake-induced fatigue analysis of horizontal axis wind turbine blade," Renewable Energy, Elsevier, vol. 116(PA), pages 423-437.
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    10. Qian, Yaoru & Wang, Tongguang & Yuan, Yiping & Zhang, Yuquan, 2020. "Comparative study on wind turbine wakes using a modified partially-averaged Navier-Stokes method and large eddy simulation," Energy, Elsevier, vol. 206(C).
    11. Victor P. Stein & Hans-Jakob Kaltenbach, 2022. "Validation of a Large-Eddy Simulation Approach for Prediction of the Ground Roughness Influence on Wind Turbine Wakes," Energies, MDPI, vol. 15(7), pages 1-25, April.
    12. Gao, Zhiteng & Li, Ye & Wang, Tongguang & Shen, Wenzhong & Zheng, Xiaobo & Pröbsting, Stefan & Li, Deshun & Li, Rennian, 2021. "Modelling the nacelle wake of a horizontal-axis wind turbine under different yaw conditions," Renewable Energy, Elsevier, vol. 172(C), pages 263-275.
    13. Micallef, Daniel & Rezaeiha, Abdolrahim, 2021. "Floating offshore wind turbine aerodynamics: Trends and future challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    14. Rezaeiha, Abdolrahim & Micallef, Daniel, 2021. "Wake interactions of two tandem floating offshore wind turbines: CFD analysis using actuator disc model," Renewable Energy, Elsevier, vol. 179(C), pages 859-876.
    15. 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.
    16. Li, Qing'an & Maeda, Takao & Kamada, Yasunari & Mori, Naoya, 2017. "Investigation of wake characteristics of a Horizontal Axis Wind Turbine in vertical axis direction with field experiments," Energy, Elsevier, vol. 141(C), pages 262-272.
    17. Sarlak, H. & Nishino, T. & Martínez-Tossas, L.A. & Meneveau, C. & Sørensen, J.N., 2016. "Assessment of blockage effects on the wake characteristics and power of wind turbines," Renewable Energy, Elsevier, vol. 93(C), pages 340-352.
    18. Stevens, Richard J.A.M. & Martínez-Tossas, Luis A. & Meneveau, Charles, 2018. "Comparison of wind farm large eddy simulations using actuator disk and actuator line models with wind tunnel experiments," Renewable Energy, Elsevier, vol. 116(PA), pages 470-478.

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