IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v156y2020icp328-341.html
   My bibliography  Save this article

Self-similarity in the wake of a semi-submersible offshore wind turbine considering the interaction with the wake of supporting platform

Author

Listed:
  • Xiong, Xue-Lu
  • Lyu, Pin
  • Chen, Wen-Li
  • Li, Hui

Abstract

An experimental study of the wake characteristics of a semi-submersible offshore wind turbine model was performed in a wind tunnel and wave flume. The velocity distribution in the vertical direction was obtained with a four-hole pressure probe. First, a self-similarity analysis of the streamwise velocity deficit disclosed the inability of the Gaussian-like wake models for predicting the velocity deficit in regions influenced by the platform. The shelter model can be adopted for the consideration of the platform wake. And the linear self-similarity of the velocity deficit caused by the platform also suggests that a linear model is feasible. Moreover, recently-discovered existence and analytical solution of the Reynolds stress self-similarity in the turbine wake were confirmed experimentally in this study. As the wake develops, the center of the Reynolds stress increment profiles drifts upward while the center of mean velocity deficit profiles remains at the same height. Furthermore, energy transport analysis confirmed the interaction effects between the rotor wake and platform wake. The results of this study will be useful for the design of the whole wind farm with more accuracy, which considers the influence of the platform on the flow field between neighbor wind turbines.

Suggested Citation

  • Xiong, Xue-Lu & Lyu, Pin & Chen, Wen-Li & Li, Hui, 2020. "Self-similarity in the wake of a semi-submersible offshore wind turbine considering the interaction with the wake of supporting platform," Renewable Energy, Elsevier, vol. 156(C), pages 328-341.
    • Handle: RePEc:eee:renene:v:156:y:2020:i:c:p:328-341
    DOI: 10.1016/j.renene.2020.04.071
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148120306030
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2020.04.071?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. Mahdi Abkar & Jens Nørkær Sørensen & Fernando Porté-Agel, 2018. "An Analytical Model for the Effect of Vertical Wind Veer on Wind Turbine Wakes," Energies, MDPI, vol. 11(7), pages 1-10, July.
    2. Pin Lyu & Wen-Li Chen & Hui Li & Lian Shen, 2019. "A Numerical Study on the Development of Self-Similarity in a Wind Turbine Wake Using an Improved Pseudo-Spectral Large-Eddy Simulation Solver," Energies, MDPI, vol. 12(4), pages 1-24, February.
    3. 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.
    4. Cheng, Yu & Zhang, Mingming & Zhang, Ziliang & Xu, Jianzhong, 2019. "A new analytical model for wind turbine wakes based on Monin-Obukhov similarity theory," Applied Energy, Elsevier, vol. 239(C), pages 96-106.
    5. Bastankhah, Majid & Porté-Agel, Fernando, 2014. "A new analytical model for wind-turbine wakes," Renewable Energy, Elsevier, vol. 70(C), pages 116-123.
    6. Wen, Binrong & Dong, Xingjian & Tian, Xinliang & Peng, Zhike & Zhang, Wenming & Wei, Kexiang, 2018. "The power performance of an offshore floating wind turbine in platform pitching motion," Energy, Elsevier, vol. 154(C), pages 508-521.
    7. Rockel, Stanislav & Peinke, Joachim & Hölling, Michael & Cal, Raúl Bayoán, 2016. "Wake to wake interaction of floating wind turbine models in free pitch motion: An eddy viscosity and mixing length approach," Renewable Energy, Elsevier, vol. 85(C), pages 666-676.
    8. Mason-Jones, A. & O'Doherty, D.M. & Morris, C.E. & O'Doherty, T., 2013. "Influence of a velocity profile & support structure on tidal stream turbine performance," Renewable Energy, Elsevier, vol. 52(C), pages 23-30.
    9. Deepu Dilip & Fernando Porté-Agel, 2017. "Wind Turbine Wake Mitigation through Blade Pitch Offset," Energies, MDPI, vol. 10(6), pages 1-17, May.
    10. Ge, Mingwei & Wu, Ying & Liu, Yongqian & Yang, Xiang I.A., 2019. "A two-dimensional Jensen model with a Gaussian-shaped velocity deficit," Renewable Energy, Elsevier, vol. 141(C), pages 46-56.
    11. Ishihara, Takeshi & Zhang, Shining, 2019. "Prediction of dynamic response of semi-submersible floating offshore wind turbine using augmented Morison's equation with frequency dependent hydrodynamic coefficients," Renewable Energy, Elsevier, vol. 131(C), pages 1186-1207.
    12. Wen, Binrong & Tian, Xinliang & Dong, Xingjian & Peng, Zhike & Zhang, Wenming, 2017. "Influences of surge motion on the power and thrust characteristics of an offshore floating wind turbine," Energy, Elsevier, vol. 141(C), pages 2054-2068.
    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, Xinbao & Cai, Chang & Cai, Shang-Gui & Wang, Tengyuan & Wang, Zekun & Song, Juanjuan & Rong, Xiaomin & Li, Qing'an, 2023. "A review of aerodynamic and wake characteristics of floating offshore wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 175(C).
    2. Zhang, Huan & Ge, Mingwei & Liu, Yongqian & Yang, Xiang I.A., 2021. "A new coupled model for the equivalent roughness heights of wind farms," Renewable Energy, Elsevier, vol. 171(C), pages 34-46.
    3. Wen, Binrong & Tian, Xinliang & Zhang, Qi & Dong, Xingjian & Peng, Zhike & Zhang, Wenming & Wei, Kexiang, 2019. "Wind shear effect induced by the platform pitch motion of a spar-type floating wind turbine," Renewable Energy, Elsevier, vol. 135(C), pages 1186-1199.
    4. Ziyu Zhang & Peng Huang & Haocheng Sun, 2020. "A Novel Analytical Wake Model with a Cosine-Shaped Velocity Deficit," Energies, MDPI, vol. 13(13), pages 1-20, June.
    5. Wang, Yangwei & Lin, Jiahuan & Zhang, Jun, 2022. "Investigation of a new analytical wake prediction method for offshore floating wind turbines considering an accurate incoming wind flow," Renewable Energy, Elsevier, vol. 185(C), pages 827-849.
    6. 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.
    7. Mohammadreza Mohammadi & Majid Bastankhah & Paul Fleming & Matthew Churchfield & Ervin Bossanyi & Lars Landberg & Renzo Ruisi, 2022. "Curled-Skewed Wakes behind Yawed Wind Turbines Subject to Veered Inflow," Energies, MDPI, vol. 15(23), pages 1-16, December.
    8. Subbulakshmi, A. & Verma, Mohit & Keerthana, M. & Sasmal, Saptarshi & Harikrishna, P. & Kapuria, Santosh, 2022. "Recent advances in experimental and numerical methods for dynamic analysis of floating offshore wind turbines — An integrated review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 164(C).
    9. 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.
    10. 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.
    11. 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).
    12. 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.
    13. 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.
    14. 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).
    15. Fang, Yuan & Li, Gen & Duan, Lei & Han, Zhaolong & Zhao, Yongsheng, 2021. "Effect of surge motion on rotor aerodynamics and wake characteristics of a floating horizontal-axis wind turbine," Energy, Elsevier, vol. 218(C).
    16. Zhou, Huanyu & Qiu, Yingning & Feng, Yanhui & Liu, Jing, 2022. "Power prediction of wind turbine in the wake using hybrid physical process and machine learning models," Renewable Energy, Elsevier, vol. 198(C), pages 568-586.
    17. Shuolin Xiao & Di Yang, 2019. "Large-Eddy Simulation-Based Study of Effect of Swell-Induced Pitch Motion on Wake-Flow Statistics and Power Extraction of Offshore Wind Turbines," Energies, MDPI, vol. 12(7), pages 1-17, April.
    18. 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.
    19. Michael F. Howland & John O. Dabiri, 2020. "Influence of Wake Model Superposition and Secondary Steering on Model-Based Wake Steering Control with SCADA Data Assimilation," Energies, MDPI, vol. 14(1), pages 1-20, December.
    20. Dou, Bingzheng & Guala, Michele & Lei, Liping & Zeng, Pan, 2019. "Wake model for horizontal-axis wind and hydrokinetic turbines in yawed conditions," Applied Energy, Elsevier, vol. 242(C), pages 1383-1395.

    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:156:y:2020:i:c:p:328-341. 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.