IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v334y2025ics0360544225030245.html

Effect of wind–wave angle on the power production and wake characteristics of an offshore wind farm at various wave ages

Author

Listed:
  • Nguyen, Van-Hoang
  • Cao, Van-Long
  • Shen, Lian
  • Park, Sung Goon

Abstract

The turbine wake and performance of an offshore wind farm are strongly influenced by wind direction and sea state, where significant knowledge gaps remain. To address the research need, the present study focuses on the effects of wind–wave angle and wave age on the wind farm performance and turbine wake characteristics using large-eddy simulation and an actuator line model. We investigate the influences of swell at various wave ages (c/u∗≈30, 60 and 90, where c is the wave phase speed and u∗ is the airflow friction velocity) and different wind–wave angles (α0=0∘–180°). Simulation results indicate that the swell following wind substantially enhances the wind farm power output and wake velocity at c/u∗≈90 compared with those at c/u∗≈30 and 60. For the effect of wind–wave angle, wind farm power output increases by approximately 50.8%, 55.3%, and 75.7% at α0=45∘, 90°, and 135°, respectively, whereas it decreases by 4.3% at α0=180∘ compared to the no-swell case. This enhancement of wind farm power output is attributed to the wake deflection. On the turbine wake characteristics, it is found that the wake is deflected considerably from the wind direction due to the deflection by lateral and oblique swells, resulting in an additional lateral shift in the wake trajectory. Low- and high-speed streaky structures are observed on the sides of the wake deflection line, which are associated with high turbulent kinetic energy there.

Suggested Citation

  • Nguyen, Van-Hoang & Cao, Van-Long & Shen, Lian & Park, Sung Goon, 2025. "Effect of wind–wave angle on the power production and wake characteristics of an offshore wind farm at various wave ages," Energy, Elsevier, vol. 334(C).
  • Handle: RePEc:eee:energy:v:334:y:2025:i:c:s0360544225030245
    DOI: 10.1016/j.energy.2025.137382
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544225030245
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2025.137382?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Yang, Haoze & Ge, Mingwei & Abkar, Mahdi & Yang, Xiang I.A., 2022. "Large-eddy simulation study of wind turbine array above swell sea," Energy, Elsevier, vol. 256(C).
    2. Singh, Ronit K. & Ahmed, M. Rafiuddin, 2013. "Blade design and performance testing of a small wind turbine rotor for low wind speed applications," Renewable Energy, Elsevier, vol. 50(C), pages 812-819.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Zheng, Chong-wei & Wu, Di & Wu, Hai-lang & Guo, Jing & Shen, Chong & Tian, Chuan & Tian, Xin-long & Xiao, Zi-niu & Zhou, Wen & Li, Chong-yin, 2022. "Propagation and attenuation of swell energy in the Pacific Ocean," Renewable Energy, Elsevier, vol. 188(C), pages 750-764.
    8. Castro-Santos, Laura & Martins, Elson & Guedes Soares, C., 2017. "Economic comparison of technological alternatives to harness offshore wind and wave energies," Energy, Elsevier, vol. 140(P1), pages 1121-1130.
    9. Boukhezzar, B. & Lupu, L. & Siguerdidjane, H. & Hand, M., 2007. "Multivariable control strategy for variable speed, variable pitch wind turbines," Renewable Energy, Elsevier, vol. 32(8), pages 1273-1287.
    10. Yang, Haoze & Ge, Mingwei & Gu, Bo & Du, Bowen & Liu, Yongqian, 2022. "The effect of swell on marine atmospheric boundary layer and the operation of an offshore wind turbine," Energy, Elsevier, vol. 244(PB).
    11. Esteban, M. Dolores & Diez, J. Javier & López, Jose S. & Negro, Vicente, 2011. "Why offshore wind energy?," Renewable Energy, Elsevier, vol. 36(2), pages 444-450.
    12. Zheng, C.W. & Li, C.Y., 2017. "Propagation characteristic and intraseasonal oscillation of the swell energy of the Indian Ocean," Applied Energy, Elsevier, vol. 197(C), pages 342-353.
    13. Chen, Guang & Liang, Xi-Feng & Li, Xiao-Bai, 2022. "Modelling of wake dynamics and instabilities of a floating horizontal-axis wind turbine under surge motion," Energy, Elsevier, vol. 239(PB).
    14. Arabgolarcheh, Alireza & Jannesarahmadi, Sahar & Benini, Ernesto, 2022. "Modeling of near wake characteristics in floating offshore wind turbines using an actuator line method," Renewable Energy, Elsevier, vol. 185(C), pages 871-887.
    15. Kyle, Ryan & Lee, Yeaw Chu & Früh, Wolf-Gerrit, 2020. "Propeller and vortex ring state for floating offshore wind turbines during surge," Renewable Energy, Elsevier, vol. 155(C), pages 645-657.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wei, Lai & Wei, Juan & Huang, Sheng & Zhang, Qian & Wang, Jinhao & Li, Canbing & Wang, Shuaifeng & Wei, Jiaheng, 2025. "Optimal decentralized power control considering wide wind speed range for wind farm based on rotor speed dominant," Energy, Elsevier, vol. 337(C).

    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. Yang, Haoze & Ge, Mingwei & Abkar, Mahdi & Yang, Xiang I.A., 2022. "Large-eddy simulation study of wind turbine array above swell sea," Energy, Elsevier, vol. 256(C).
    2. Yang, Xuefeng & Yu, Peining & Sui, Yi & Li, Sunwei & Chen, Shengli, 2026. "Effects of tide-induced variation of hub height on the power of wind turbine array: A LES study," Renewable Energy, Elsevier, vol. 256(PF).
    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. Souaiby, Marwa & Porté-Agel, Fernando, 2024. "An improved analytical framework for flow prediction inside and downstream of wind farms," Renewable Energy, Elsevier, vol. 225(C).
    5. 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).
    6. Wang, Yan & Lu, Pan & Zhou, Yongze & Guan, Ronghu & Li, Rennian, 2025. "Insight into the impact of turbine-array configurations on the power output and wake effects of a finite-size wind farm," Renewable Energy, Elsevier, vol. 255(C).
    7. Yang, Lin & Liao, Kangping & Ma, Qingwei & Ma, Gang & Sun, Hanbing, 2023. "Investigation of wake characteristics of floating offshore wind turbine with control strategy using actuator curve embedding method," Renewable Energy, Elsevier, vol. 218(C).
    8. Yang, Kun & Deng, Xiaowei & Ti, Zilong & Yang, Shanghui & Huang, Senbin & Wang, Yuhang, 2023. "A data-driven layout optimization framework of large-scale wind farms based on machine learning," Renewable Energy, Elsevier, vol. 218(C).
    9. He, Zixiao & Yang, Xudong & Sun, Haiying, 2026. "A review on modeling, simulation and experiment of dynamic wake effect of floating offshore wind turbines," Applied Energy, Elsevier, vol. 406(C).
    10. Amarloo, Ali & Zehtabiyan-Rezaie, Navid & Abkar, Mahdi, 2024. "A progressive data-augmented RANS model for enhanced wind-farm simulations," Energy, Elsevier, vol. 313(C).
    11. 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).
    12. Fan, Zhixin & Zhu, Caichao, 2019. "The optimization and the application for the wind turbine power-wind speed curve," Renewable Energy, Elsevier, vol. 140(C), pages 52-61.
    13. Ti, Zilong & Deng, Xiao Wei & Yang, Hongxing, 2020. "Wake modeling of wind turbines using machine learning," Applied Energy, Elsevier, vol. 257(C).
    14. Mian, H.H. & Machot, F.A. & Ullah, H. & Keprate, A. & Siddiqui, M.S., 2025. "Advances in computational intelligence for floating offshore wind turbines aerodynamics: Current state review and future potential," Renewable and Sustainable Energy Reviews, Elsevier, vol. 224(C).
    15. 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.
    16. Duan, Guiyue & Gattari, Daniele & Porté-Agel, Fernando, 2025. "Theoretical and experimental study on power performance and wake characteristics of a floating wind turbine under pitch motion," Applied Energy, Elsevier, vol. 378(PA).
    17. Dou, Bingzheng & Qu, Timing & Lei, Liping & Zeng, Pan, 2020. "Optimization of wind turbine yaw angles in a wind farm using a three-dimensional yawed wake model," Energy, Elsevier, vol. 209(C).
    18. Deepu Dilip & Fernando Porté-Agel, 2017. "Wind Turbine Wake Mitigation through Blade Pitch Offset," Energies, MDPI, vol. 10(6), pages 1-17, May.
    19. Yang, Shanghui & Deng, Xiaowei & Li, Qinglan, 2025. "A joint optimization framework for power and fatigue life based on cooperative wake steering of wind farm," Energy, Elsevier, vol. 319(C).
    20. Yang, Haoze & Ge, Mingwei & Gu, Bo & Du, Bowen & Liu, Yongqian, 2022. "The effect of swell on marine atmospheric boundary layer and the operation of an offshore wind turbine," Energy, Elsevier, vol. 244(PB).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:energy:v:334:y:2025:i:c:s0360544225030245. 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/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.