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A concurrent precursor inflow method for Large Eddy Simulations and applications to finite length wind farms

Author

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  • Stevens, Richard J.A.M.
  • Graham, Jason
  • Meneveau, Charles

Abstract

In order to enable simulations of developing wind turbine array boundary layers with highly realistic inflow conditions a concurrent precursor method for Large Eddy Simulations is proposed. In this method we consider two domains simultaneously, i.e. in one domain a turbulent Atmospheric Boundary Layer (ABL) without wind turbines is simulated in order to generate the turbulent inflow conditions for a second domain in which the wind turbines are placed. The benefit of this approach is that a) it avoids the need for large databases in which the turbulent inflow conditions are stored and the correspondingly slow I/O operations and b) we are sure that the simulations are not negatively affected by statically swept fixed inflow fields or synthetic fields lacking the proper ABL coherent structures. Sample applications are presented, in which, in agreement with field data a strong decrease of the power output of downstream wind-turbines with respect to the first row of wind-turbines is observed for perfectly aligned inflow.

Suggested Citation

  • Stevens, Richard J.A.M. & Graham, Jason & Meneveau, Charles, 2014. "A concurrent precursor inflow method for Large Eddy Simulations and applications to finite length wind farms," Renewable Energy, Elsevier, vol. 68(C), pages 46-50.
  • Handle: RePEc:eee:renene:v:68:y:2014:i:c:p:46-50
    DOI: 10.1016/j.renene.2014.01.024
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    Citations

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    Cited by:

    1. Carl R. Shapiro & Genevieve M. Starke & Charles Meneveau & Dennice F. Gayme, 2019. "A Wake Modeling Paradigm for Wind Farm Design and Control," Energies, MDPI, vol. 12(15), pages 1-19, August.
    2. 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.
    3. Amiri, Mojtaba Maali & Shadman, Milad & Estefen, Segen F., 2024. "A review of physical and numerical modeling techniques for horizontal-axis wind turbine wakes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 193(C).
    4. Khan, Mehtab Ahmad & Javed, Adeel & Shakir, Sehar & Syed, Abdul Haseeb, 2021. "Optimization of a wind farm by coupled actuator disk and mesoscale models to mitigate neighboring wind farm wake interference from repowering perspective," Applied Energy, Elsevier, vol. 298(C).
    5. Zhang, Ziyu & Huang, Peng & Bitsuamlak, Girma & Cao, Shuyang, 2024. "Large-eddy simulation of upwind-hill effects on wind-turbine wakes and power performance," Energy, Elsevier, vol. 294(C).
    6. Liu, Luoqin & Stevens, Richard J.A.M., 2021. "Effects of atmospheric stability on the performance of a wind turbine located behind a three-dimensional hill," Renewable Energy, Elsevier, vol. 175(C), pages 926-935.
    7. 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.
    8. Eidi, Ali & Ghiassi, Reza & Yang, Xiang & Abkar, Mahdi, 2021. "Model-form uncertainty quantification in RANS simulations of wakes and power losses in wind farms," Renewable Energy, Elsevier, vol. 179(C), pages 2212-2223.
    9. Jay P. Goit & Wim Munters & Johan Meyers, 2016. "Optimal Coordinated Control of Power Extraction in LES of a Wind Farm with Entrance Effects," Energies, MDPI, vol. 9(1), pages 1-20, January.
    10. Li, Li & Huang, Zhi & Ge, Mingwei & Zhang, Qiying, 2022. "A novel three-dimensional analytical model of the added streamwise turbulence intensity for wind-turbine wakes," Energy, Elsevier, vol. 238(PB).
    11. Lignarolo, Lorenzo E.M. & Mehta, Dhruv & Stevens, Richard J.A.M. & Yilmaz, Ali Emre & van Kuik, Gijs & Andersen, Søren J. & Meneveau, Charles & Ferreira, Carlos J. & Ragni, Daniele & Meyers, Johan & v, 2016. "Validation of four LES and a vortex model against stereo-PIV measurements in the near wake of an actuator disc and a wind turbine," Renewable Energy, Elsevier, vol. 94(C), pages 510-523.
    12. Xiaoshu Lü & Tao Lu & Tong Yang & Heidi Salonen & Zhenxue Dai & Peter Droege & Hongbing Chen, 2021. "Improving the Energy Efficiency of Buildings Based on Fluid Dynamics Models: A Critical Review," Energies, MDPI, vol. 14(17), pages 1-23, August.
    13. Yang, Di & Meneveau, Charles & Shen, Lian, 2014. "Effect of downwind swells on offshore wind energy harvesting – A large-eddy simulation study," Renewable Energy, Elsevier, vol. 70(C), pages 11-23.
    14. Strickland, Jessica M.I. & Gadde, Srinidhi N. & Stevens, Richard J.A.M., 2022. "Wind farm blockage in a stable atmospheric boundary layer," Renewable Energy, Elsevier, vol. 197(C), pages 50-58.
    15. Kevin A. Adkins & Adrian Sescu, 2022. "Wind Farms and Humidity," Energies, MDPI, vol. 15(7), pages 1-15, April.
    16. Ge, Mingwei & Gayme, Dennice F. & Meneveau, Charles, 2021. "Large-eddy simulation of wind turbines immersed in the wake of a cube-shaped building," Renewable Energy, Elsevier, vol. 163(C), pages 1063-1077.

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