IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v221y2024ics0960148123017226.html
   My bibliography  Save this article

Comparison of the dynamic wake meandering model against large eddy simulation for horizontal and vertical steering of wind turbine wakes

Author

Listed:
  • Rivera-Arreba, Irene
  • Li, Zhaobin
  • Yang, Xiaolei
  • Bachynski-Polić, Erin E.

Abstract

Accurately predicting the evolution of wake is crucial for power output and structural load estimation in wind farms. This study aims to validate the dynamic wake meandering (DWM) model, an efficient mid-fidelity wake model, against large eddy simulation (LES). The predictive capabilities of the DWM model for various wake properties, namely time-averaged wake deficit, mean wake center deflection, amplitude, and frequency spectrum of wake meandering, are comprehensively analyzed using the IEA 15MW reference wind turbine under different yaw and tilt misalignment angles. Two turbulent inflows with varying shear and turbulence intensity levels are considered. The comparison highlights the significance of the filter size (Cmeand) in DWM as a key parameter determining simultaneously the time-averaged wake deflection and meandering amplitude, with optimal values differing for horizontal and vertical wake displacements. When the appropriate Cmeand values are selected, the implementation of the DWM model in FAST.Farm demonstrates good agreement with LES data, particularly concerning time-averaged wake deficit, wake centerline deflection, and wake meandering amplitude at eight rotor diameters downstream. However, the DWM model tends to overestimate the energy in the lower frequency region with Strouhal’s number less than 0.1 and underestimate the wake oscillation induced by the shear-layer at higher frequencies, even though the wake motion standard deviation is accurately reproduced if the polar grid size is properly adjusted. Furthermore, the influence of the ground effect on downward wake deflection through tilt control is revealed. These findings clearly demonstrate the strengths and weaknesses of the current DWM model and can serve as a reference for the development of advanced wake models.

Suggested Citation

  • Rivera-Arreba, Irene & Li, Zhaobin & Yang, Xiaolei & Bachynski-Polić, Erin E., 2024. "Comparison of the dynamic wake meandering model against large eddy simulation for horizontal and vertical steering of wind turbine wakes," Renewable Energy, Elsevier, vol. 221(C).
    • Handle: RePEc:eee:renene:v:221:y:2024:i:c:s0960148123017226
    DOI: 10.1016/j.renene.2023.119807
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148123017226
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2023.119807?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. 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.
    2. Fleming, Paul A. & Gebraad, Pieter M.O. & Lee, Sang & van Wingerden, Jan-Willem & Johnson, Kathryn & Churchfield, Matt & Michalakes, John & Spalart, Philippe & Moriarty, Patrick, 2014. "Evaluating techniques for redirecting turbine wakes using SOWFA," Renewable Energy, Elsevier, vol. 70(C), pages 211-218.
    3. 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.
    4. Guo-Wei Qian & Takeshi Ishihara, 2018. "A New Analytical Wake Model for Yawed Wind Turbines," Energies, MDPI, vol. 11(3), pages 1-24, March.
    5. Michael F. Howland & Jesús Bas Quesada & Juan José Pena Martínez & Felipe Palou Larrañaga & Neeraj Yadav & Jasvipul S. Chawla & Varun Sivaram & John O. Dabiri, 2022. "Collective wind farm operation based on a predictive model increases utility-scale energy production," Nature Energy, Nature, vol. 7(9), pages 818-827, September.
    6. Dong, Guodan & Li, Zhaobin & Qin, Jianhua & Yang, Xiaolei, 2022. "Predictive capability of actuator disk models for wakes of different wind turbine designs," Renewable Energy, Elsevier, vol. 188(C), pages 269-281.
    7. Xiaolei Yang & Fotis Sotiropoulos, 2019. "A Review on the Meandering of Wind Turbine Wakes," Energies, MDPI, vol. 12(24), pages 1-20, December.
    8. Johlas, Hannah M. & Schmidt, David P. & Lackner, Matthew A., 2022. "Large eddy simulations of curled wakes from tilted wind turbines," Renewable Energy, Elsevier, vol. 188(C), pages 349-360.
    9. Zhang, Yi & Li, Zhaobin & Liu, Xiaohao & Sotiropoulos, Fotis & Yang, Xiaolei, 2023. "Turbulence in waked wind turbine wakes: Similarity and empirical formulae," Renewable Energy, Elsevier, vol. 209(C), pages 27-41.
    10. Zhaobin Li & Xiaohao Liu & Xiaolei Yang, 2022. "Review of Turbine Parameterization Models for Large-Eddy Simulation of Wind Turbine Wakes," Energies, MDPI, vol. 15(18), pages 1-28, September.
    11. Jiarong Hong & Mostafa Toloui & Leonardo P. Chamorro & Michele Guala & Kevin Howard & Sean Riley & James Tucker & Fotis Sotiropoulos, 2014. "Natural snowfall reveals large-scale flow structures in the wake of a 2.5-MW wind turbine," Nature Communications, Nature, vol. 5(1), pages 1-9, September.
    12. Yang, Xiaolei & Pakula, Maggie & Sotiropoulos, Fotis, 2018. "Large-eddy simulation of a utility-scale wind farm in complex terrain," Applied Energy, Elsevier, vol. 229(C), pages 767-777.
    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. Zhaobin Li & Xiaohao Liu & Xiaolei Yang, 2022. "Review of Turbine Parameterization Models for Large-Eddy Simulation of Wind Turbine Wakes," Energies, MDPI, vol. 15(18), pages 1-28, September.
    2. Yunliang Li & Zhaobin Li & Zhideng Zhou & Xiaolei Yang, 2023. "Large-Eddy Simulation of Wind Turbine Wakes in Forest Terrain," Sustainability, MDPI, vol. 15(6), pages 1-23, March.
    3. Mou Lin & Fernando Porté-Agel, 2019. "Large-Eddy Simulation of Yawed Wind-Turbine Wakes: Comparisons with Wind Tunnel Measurements and Analytical Wake Models," Energies, MDPI, vol. 12(23), pages 1-18, November.
    4. 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).
    5. Wang, Qiang & Luo, Kun & Yuan, Renyu & Wang, Shuai & Fan, Jianren & Cen, Kefa, 2020. "A multiscale numerical framework coupled with control strategies for simulating a wind farm in complex terrain," Energy, Elsevier, vol. 203(C).
    6. De-Zhi Wei & Ni-Na Wang & De-Cheng Wan, 2021. "Modelling Yawed Wind Turbine Wakes: Extension of a Gaussian-Based Wake Model," Energies, MDPI, vol. 14(15), pages 1-26, July.
    7. He, Ruiyang & Yang, Hongxing & Lu, Lin & Gao, Xiaoxia, 2024. "Site-specific wake steering strategy for combined power enhancement and fatigue mitigation within wind farms," Renewable Energy, Elsevier, vol. 225(C).
    8. Shen, Wen Zhong & Lin, Jian Wei & Jiang, Yu Hang & Feng, Ju & Cheng, Li & Zhu, Wei Jun, 2023. "A novel yaw wake model for wind farm control applications," Renewable Energy, Elsevier, vol. 218(C).
    9. Rubel C. Das & Yu-Lin Shen, 2023. "Analysis of Wind Farms under Different Yaw Angles and Wind Speeds," Energies, MDPI, vol. 16(13), pages 1-19, June.
    10. Arabgolarcheh, Alireza & Rouhollahi, Amirhossein & Benini, Ernesto, 2023. "Analysis of middle-to-far wake behind floating offshore wind turbines in the presence of multiple platform motions," Renewable Energy, Elsevier, vol. 208(C), pages 546-560.
    11. Zhu, Xiaoxun & Chen, Yao & Xu, Shinai & Zhang, Shaohai & Gao, Xiaoxia & Sun, Haiying & Wang, Yu & Zhao, Fei & Lv, Tiancheng, 2023. "Three-dimensional non-uniform full wake characteristics for yawed wind turbine with LiDAR-based experimental verification," Energy, Elsevier, vol. 270(C).
    12. Hegazy, Amr & Blondel, Frédéric & Cathelain, Marie & Aubrun, Sandrine, 2022. "LiDAR and SCADA data processing for interacting wind turbine wakes with comparison to analytical wake models," Renewable Energy, Elsevier, vol. 181(C), pages 457-471.
    13. Sang Lee & Matthew Churchfield & Frederick Driscoll & Senu Sirnivas & Jason Jonkman & Patrick Moriarty & Bjόrn Skaare & Finn Gunnar Nielsen & Erik Byklum, 2018. "Load Estimation of Offshore Wind Turbines," Energies, MDPI, vol. 11(7), pages 1-15, July.
    14. Esmail Mahmoodi & Mohammad Khezri & Arash Ebrahimi & Uwe Ritschel & Leonardo P. Chamorro & Ali Khanjari, 2023. "A Simple Model for Wake-Induced Aerodynamic Interaction of Wind Turbines," Energies, MDPI, vol. 16(15), pages 1-13, July.
    15. Jagdeep Singh & Jahrul M Alam, 2023. "Large-Eddy Simulation of Utility-Scale Wind Farm Sited over Complex Terrain," Energies, MDPI, vol. 16(16), pages 1-26, August.
    16. Andrés Guggeri & Martín Draper, 2019. "Large Eddy Simulation of an Onshore Wind Farm with the Actuator Line Model Including Wind Turbine’s Control below and above Rated Wind Speed," Energies, MDPI, vol. 12(18), pages 1-21, September.
    17. Feng, Dachuan & Li, Larry K.B. & Gupta, Vikrant & Wan, Minping, 2022. "Componentwise influence of upstream turbulence on the far-wake dynamics of wind turbines," Renewable Energy, Elsevier, vol. 200(C), pages 1081-1091.
    18. Tian, Linlin & Song, Yilei & Zhao, Ning & Shen, Wenzhong & Zhu, Chunling & Wang, Tongguang, 2020. "Effects of turbulence modelling in AD/RANS simulations of single wind & tidal turbine wakes and double wake interactions," Energy, Elsevier, vol. 208(C).
    19. Harsh S. Dhiman & Dipankar Deb & Vlad Muresan & Valentina E. Balas, 2019. "Wake Management in Wind Farms: An Adaptive Control Approach," Energies, MDPI, vol. 12(7), pages 1-18, April.
    20. Zhaobin Li & Xiaolei Yang, 2020. "Evaluation of Actuator Disk Model Relative to Actuator Surface Model for Predicting Utility-Scale Wind Turbine Wakes," Energies, MDPI, vol. 13(14), pages 1-18, July.

    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:221:y:2024:i:c:s0960148123017226. 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.