IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v75y2015icp945-955.html
   My bibliography  Save this article

Modeling turbine wakes and power losses within a wind farm using LES: An application to the Horns Rev offshore wind farm

Author

Listed:
  • Wu, Yu-Ting
  • Porté-Agel, Fernando

Abstract

A modeling framework is proposed and validated to simulate turbine wakes and associated power losses in wind farms. It combines the large-eddy simulation (LES) technique with blade element theory and a turbine-model-specific relationship between shaft torque and rotational speed. In the LES, the turbulent subgrid-scale stresses are parameterized with a tuning-free Lagrangian scale-dependent dynamic model. The turbine-induced forces and turbine-generated power are modeled using a recently developed actuator-disk model with rotation (ADM-R), which adopts blade element theory to calculate the lift and drag forces (that produce thrust, rotor shaft torque and power) based on the local simulated flow and the blade characteristics. In order to predict simultaneously the turbine angular velocity and the turbine-induced forces (and thus the power output), a new iterative dynamic procedure is developed to couple the ADM-R turbine model with a relationship between shaft torque and rotational speed. This relationship, which is unique for a given turbine model and independent of the inflow condition, is derived from simulations of a stand-alone wind turbine in conditions for which the thrust coefficient can be validated. Comparison with observed power data from the Horns Rev wind farm shows that better power predictions are obtained with the dynamic ADM-R than with the standard ADM, which assumes a uniform thrust distribution and ignores the torque effect on the turbine wakes and rotor power. The results are also compared with the power predictions obtained using two commercial wind-farm design tools (WindSim and WAsP). These models are found to underestimate the power output compared with the results from the proposed LES framework.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:renene:v:75:y:2015:i:c:p:945-955
    DOI: 10.1016/j.renene.2014.06.019
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148114003590
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2014.06.019?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yu-Ting Wu & Fernando Porté-Agel, 2012. "Atmospheric Turbulence Effects on Wind-Turbine Wakes: An LES Study," Energies, MDPI, vol. 5(12), pages 1-23, December.
    2. Fernando Porté-Agel & Yu-Ting Wu & Chang-Hung Chen, 2013. "A Numerical Study of the Effects of Wind Direction on Turbine Wakes and Power Losses in a Large Wind Farm," Energies, MDPI, vol. 6(10), pages 1-17, October.
    3. Leonardo P. Chamorro & Fernando Porté-Agel, 2011. "Turbulent Flow Inside and Above a Wind Farm: A Wind-Tunnel Study," Energies, MDPI, vol. 4(11), pages 1-21, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pankaj K. Jha & Earl P. N. Duque & Jessica L. Bashioum & Sven Schmitz, 2015. "Unraveling the Mysteries of Turbulence Transport in a Wind Farm," Energies, MDPI, vol. 8(7), pages 1-29, June.
    2. Majid Bastankhah & Fernando Porté-Agel, 2017. "A New Miniature Wind Turbine for Wind Tunnel Experiments. Part II: Wake Structure and Flow Dynamics," Energies, MDPI, vol. 10(7), pages 1-19, July.
    3. Jacob R. West & Sanjiva K. Lele, 2020. "Wind Turbine Performance in Very Large Wind Farms: Betz Analysis Revisited," Energies, MDPI, vol. 13(5), pages 1-25, March.
    4. Nicolas Kirchner-Bossi & Fernando Porté-Agel, 2018. "Realistic Wind Farm Layout Optimization through Genetic Algorithms Using a Gaussian Wake Model," Energies, MDPI, vol. 11(12), pages 1-26, November.
    5. Nicolas Kirchner-Bossi & Fernando Porté-Agel, 2021. "Wind Farm Area Shape Optimization Using Newly Developed Multi-Objective Evolutionary Algorithms," Energies, MDPI, vol. 14(14), pages 1-25, July.
    6. Amin Niayifar & Fernando Porté-Agel, 2016. "Analytical Modeling of Wind Farms: A New Approach for Power Prediction," Energies, MDPI, vol. 9(9), pages 1-13, September.
    7. Tristan Revaz & Fernando Porté-Agel, 2021. "Large-Eddy Simulation of Wind Turbine Flows: A New Evaluation of Actuator Disk Models," Energies, MDPI, vol. 14(13), pages 1-22, June.
    8. Bastankhah, Majid & Porté-Agel, Fernando, 2014. "A new analytical model for wind-turbine wakes," Renewable Energy, Elsevier, vol. 70(C), pages 116-123.
    9. Gao, Xiaoxia & Li, Bingbing & Wang, Tengyuan & Sun, Haiying & Yang, Hongxing & Li, Yonghua & Wang, Yu & Zhao, Fei, 2020. "Investigation and validation of 3D wake model for horizontal-axis wind turbines based on filed measurements," Applied Energy, Elsevier, vol. 260(C).
    10. Deepu Dilip & Fernando Porté-Agel, 2017. "Wind Turbine Wake Mitigation through Blade Pitch Offset," Energies, MDPI, vol. 10(6), pages 1-17, May.
    11. Li, Li & Wang, Bing & Ge, Mingwei & Huang, Zhi & Li, Xintao & Liu, Yongqian, 2023. "A novel superposition method for streamwise turbulence intensity of wind-turbine wakes," Energy, Elsevier, vol. 276(C).
    12. C. A. Lopez-Villalobos & O. Rodriguez-Hernandez & R. Campos-Amezcua & Guillermo Hernandez-Cruz & O. A. Jaramillo & J. L. Mendoza, 2018. "Wind Turbulence Intensity at La Ventosa, Mexico: A Comparative Study with the IEC61400 Standards," Energies, MDPI, vol. 11(11), pages 1-19, November.
    13. Chen, Guang & Li, Xiao-Bai & Liang, Xi-Feng, 2022. "IDDES simulation of the performance and wake dynamics of the wind turbines under different turbulent inflow conditions," Energy, Elsevier, vol. 238(PB).
    14. Fan, Xiantao & Ge, Mingwei & Tan, Wei & Li, Qi, 2021. "Impacts of coexisting buildings and trees on the performance of rooftop wind turbines: An idealized numerical study," Renewable Energy, Elsevier, vol. 177(C), pages 164-180.
    15. Dar, Arslan Salim & Porté-Agel, Fernando, 2022. "Wind turbine wakes on escarpments: A wind-tunnel study," Renewable Energy, Elsevier, vol. 181(C), pages 1258-1275.
    16. Xiaolei Yang & Daniel Foti & Christopher Kelley & David Maniaci & Fotis Sotiropoulos, 2020. "Wake Statistics of Different-Scale Wind Turbines under Turbulent Boundary Layer Inflow," Energies, MDPI, vol. 13(11), pages 1-17, June.
    17. Tian, Linlin & Zhu, Weijun & Shen, Wenzhong & Song, Yilei & Zhao, Ning, 2017. "Prediction of multi-wake problems using an improved Jensen wake model," Renewable Energy, Elsevier, vol. 102(PB), pages 457-469.
    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.
    19. Cao, Lichao & Ge, Mingwei & Gao, Xiaoxia & Du, Bowen & Li, Baoliang & Huang, Zhi & Liu, Yongqian, 2022. "Wind farm layout optimization to minimize the wake induced turbulence effect on wind turbines," Applied Energy, Elsevier, vol. 323(C).
    20. Mattuella, J.M.L. & Loredo-Souza, A.M. & Oliveira, M.G.K. & Petry, A.P., 2016. "Wind tunnel experimental analysis of a complex terrain micrositing," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 110-119.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:75:y:2015:i:c:p:945-955. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.