IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i3p753-d1333787.html
   My bibliography  Save this article

A Comparative Analysis of Actuator-Based Turbine Structure Parametrizations for High-Fidelity Modeling of Utility-Scale Wind Turbines under Neutral Atmospheric Conditions

Author

Listed:
  • Christian Santoni

    (Department of Civil Engineering, Stony Brook University, Stony Brook, NY 11794, USA)

  • Fotis Sotiropoulos

    (Mechanical and Nuclear Engineering, Virginia Commonwealth University, Richmond, VA 23284, USA)

  • Ali Khosronejad

    (Department of Civil Engineering, Stony Brook University, Stony Brook, NY 11794, USA)

Abstract

This study compared the efficacy of the actuator line and actuator surface models in carrying out large-eddy simulations of a utility-scale wind turbine. A large-eddy simulation with the actuator surface and line models was employed to study the wake flow and power production of the turbine. While both the actuator models were employed for the blade representation, the nacelle was modeled using the actuator surface approach. Both of the actuator models demonstrated agreement in the mean velocity field, power production, and turbulence kinetic energy of the wake flow. Comparing the wake flow, power production, and turbulence kinetic energy results, it was found that the mean discrepancy between the two models was 0.6 % , 0.3 % , and 2.3 % , respectively. Despite the minor discrepancies, both actuator models accurately captured the hub vortex in the wake of the nacelle, evidenced by an energy peak in wind speed spectra at f / f ω ≈ 0.34 .

Suggested Citation

  • Christian Santoni & Fotis Sotiropoulos & Ali Khosronejad, 2024. "A Comparative Analysis of Actuator-Based Turbine Structure Parametrizations for High-Fidelity Modeling of Utility-Scale Wind Turbines under Neutral Atmospheric Conditions," Energies, MDPI, vol. 17(3), pages 1-16, February.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:3:p:753-:d:1333787
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/3/753/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/3/753/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Della Posta, Giacomo & Leonardi, Stefano & Bernardini, Matteo, 2022. "A two-way coupling method for the study of aeroelastic effects in large wind turbines," Renewable Energy, Elsevier, vol. 190(C), pages 971-992.
    3. Bastankhah, Majid & Porté-Agel, Fernando, 2014. "A new analytical model for wind-turbine wakes," Renewable Energy, Elsevier, vol. 70(C), pages 116-123.
    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. Wang, Tengyuan & Cai, Chang & Wang, Xinbao & Wang, Zekun & Chen, Yewen & Song, Juanjuan & Xu, Jianzhong & Zhang, Yuning & Li, Qingan, 2023. "A new Gaussian analytical wake model validated by wind tunnel experiment and LiDAR field measurements under different turbulent flow," Energy, Elsevier, vol. 271(C).
    2. Meng, Hang & Li, Li & Zhang, Jinhua, 2020. "A preliminary numerical study of the wake effects on the fatigue load for wind farm based on elastic actuator line model," Renewable Energy, Elsevier, vol. 162(C), pages 788-801.
    3. 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).
    4. Meng, Hang & Lien, Fue-Sang & Yee, Eugene & Shen, Jingfang, 2020. "Modelling of anisotropic beam for rotating composite wind turbine blade by using finite-difference time-domain (FDTD) method," Renewable Energy, Elsevier, vol. 162(C), pages 2361-2379.
    5. 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.
    6. Nicolas Tobin & Ali M. Hamed & Leonardo P. Chamorro, 2015. "An Experimental Study on the Effects ofWinglets on the Wake and Performance of a ModelWind Turbine," Energies, MDPI, vol. 8(10), pages 1-18, October.
    7. Fei Zhao & Yihan Gao & Tengyuan Wang & Jinsha Yuan & Xiaoxia Gao, 2020. "Experimental Study on Wake Evolution of a 1.5 MW Wind Turbine in a Complex Terrain Wind Farm Based on LiDAR Measurements," Sustainability, MDPI, vol. 12(6), pages 1-14, March.
    8. Li, Siyi & Zhang, Mingrui & Piggott, Matthew D., 2023. "End-to-end wind turbine wake modelling with deep graph representation learning," Applied Energy, Elsevier, vol. 339(C).
    9. Ti, Zilong & Deng, Xiao Wei & Yang, Hongxing, 2020. "Wake modeling of wind turbines using machine learning," Applied Energy, Elsevier, vol. 257(C).
    10. Siyu Tao & Andrés Feijóo & Jiemin Zhou & Gang Zheng, 2020. "Topology Design of an Offshore Wind Farm with Multiple Types of Wind Turbines in a Circular Layout," Energies, MDPI, vol. 13(3), pages 1-16, January.
    11. Zilong, Ti & Xiao Wei, Deng, 2022. "Layout optimization of offshore wind farm considering spatially inhomogeneous wave loads," Applied Energy, Elsevier, vol. 306(PA).
    12. Lam, H.F. & Peng, H.Y., 2016. "Study of wake characteristics of a vertical axis wind turbine by two- and three-dimensional computational fluid dynamics simulations," Renewable Energy, Elsevier, vol. 90(C), pages 386-398.
    13. Sun, Haiying & Yang, Hongxing, 2020. "Numerical investigation of the average wind speed of a single wind turbine and development of a novel three-dimensional multiple wind turbine wake model," Renewable Energy, Elsevier, vol. 147(P1), pages 192-203.
    14. Richard J. Foreman & Beatriz Cañadillas & Nick Robinson, 2024. "The Atmospheric Stability Dependence of Far Wakes on the Power Output of Downstream Wind Farms," Energies, MDPI, vol. 17(2), pages 1-23, January.
    15. Gu, Bo & Meng, Hang & Ge, Mingwei & Zhang, Hongtao & Liu, Xinyu, 2021. "Cooperative multiagent optimization method for wind farm power delivery maximization," Energy, Elsevier, vol. 233(C).
    16. Mingqiu Liu & Zhichang Liang & Haixiao Liu, 2022. "Numerical Investigations of Wake Expansion in the Offshore Wind Farm Using a Large Eddy Simulation," Energies, MDPI, vol. 15(6), pages 1-19, March.
    17. Ti, Zilong & Deng, Xiao Wei & Zhang, Mingming, 2021. "Artificial Neural Networks based wake model for power prediction of wind farm," Renewable Energy, Elsevier, vol. 172(C), pages 618-631.
    18. Guillem Armengol Barcos & Fernando Porté-Agel, 2023. "Enhancing Wind Farm Performance through Axial Induction and Tilt Control: Insights from Wind Tunnel Experiments," Energies, MDPI, vol. 17(1), pages 1-20, December.
    19. Jong-Hyeon Shin & Jong-Hwi Lee & Se-Myong Chang, 2019. "A Simplified Numerical Model for the Prediction of Wake Interaction in Multiple Wind Turbines," Energies, MDPI, vol. 12(21), pages 1-14, October.
    20. Xu Ning & Decheng Wan, 2019. "LES Study of Wake Meandering in Different Atmospheric Stabilities and Its Effects on Wind Turbine Aerodynamics," Sustainability, MDPI, vol. 11(24), pages 1-26, December.

    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:gam:jeners:v:17:y:2024:i:3:p:753-:d:1333787. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.