IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v185y2022icp827-849.html
   My bibliography  Save this article

Investigation of a new analytical wake prediction method for offshore floating wind turbines considering an accurate incoming wind flow

Author

Listed:
  • Wang, Yangwei
  • Lin, Jiahuan
  • Zhang, Jun

Abstract

High prediction accuracy of the wake is crucial for the aerodynamic design and layout optimization of the offshore floating wind turbine (OFWT) in a wind farm. In order to achieve this, an innovative three-dimensional (3D) analytical wake prediction method is developed for the first time. Compared with previous methods, the present one considers an accurate incoming wind flow including the environmental and structural disturbances, which is more closer to the reality. Besides, it adopts a more physically intuitive wake expansion model and a novel 3D Gaussian wake model to predict the wake. To verify this method, comparisons with the experimental data from four worldwide wind tunnels are conducted. The results are excellent from the near to far wake regions, which can prove its high prediction accuracy. Finally, based on this method, the effects of the included wind disturbances on the wake are analyzed comprehensively to reveal the internal mechanism affecting the prediction. The results show that these wind disturbances can affect the wake significantly. The present study could make a theoretical contribution to the wake modeling and the aerodynamic study of the OFWT.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:renene:v:185:y:2022:i:c:p:827-849
    DOI: 10.1016/j.renene.2021.12.060
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148121017808
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2021.12.060?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, Xiaoxia & Yang, Hongxing & Lu, Lin, 2016. "Optimization of wind turbine layout position in a wind farm using a newly-developed two-dimensional wake model," Applied Energy, Elsevier, vol. 174(C), pages 192-200.
    2. 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.
    3. Sun, Haiying & Yang, Hongxing, 2018. "Study on an innovative three-dimensional wind turbine wake model," Applied Energy, Elsevier, vol. 226(C), pages 483-493.
    4. Syed Ahmed Kabir, Ijaz Fazil & Safiyullah, Ferozkhan & Ng, E.Y.K. & Tam, Vivian W.Y., 2020. "New analytical wake models based on artificial intelligence and rivalling the benchmark full-rotor CFD predictions under both uniform and ABL inflows," Energy, Elsevier, vol. 193(C).
    5. Oh, Ki-Yong & Park, Joon-Young & Lee, Jun-Shin & Lee, JaeKyung, 2015. "Implementation of a torque and a collective pitch controller in a wind turbine simulator to characterize the dynamics at three control regions," Renewable Energy, Elsevier, vol. 79(C), pages 150-160.
    6. Jijian Lian & Ou Cai & Xiaofeng Dong & Qi Jiang & Yue Zhao, 2019. "Health Monitoring and Safety Evaluation of the Offshore Wind Turbine Structure: A Review and Discussion of Future Development," Sustainability, MDPI, vol. 11(2), pages 1-29, January.
    7. Jeon, Sanghyeon & Kim, Bumsuk & Huh, Jongchul, 2015. "Comparison and verification of wake models in an onshore wind farm considering single wake condition of the 2 MW wind turbine," Energy, Elsevier, vol. 93(P2), pages 1769-1777.
    8. Tran, Thanh Toan & Kim, Dong-Hyun, 2016. "A CFD study into the influence of unsteady aerodynamic interference on wind turbine surge motion," Renewable Energy, Elsevier, vol. 90(C), pages 204-228.
    9. Bastankhah, Majid & Porté-Agel, Fernando, 2014. "A new analytical model for wind-turbine wakes," Renewable Energy, Elsevier, vol. 70(C), pages 116-123.
    10. 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.
    11. Hur, S. & Recalde-Camacho, L. & Leithead, W.E., 2017. "Detection and compensation of anomalous conditions in a wind turbine," Energy, Elsevier, vol. 124(C), pages 74-86.
    12. Koh, J.H. & Ng, E.Y.K., 2016. "Downwind offshore wind turbines: Opportunities, trends and technical challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 797-808.
    13. Shen, Xin & Chen, Jinge & Hu, Ping & Zhu, Xiaocheng & Du, Zhaohui, 2018. "Study of the unsteady aerodynamics of floating wind turbines," Energy, Elsevier, vol. 145(C), pages 793-809.
    14. 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).
    15. Ge, Mingwei & Wu, Ying & Liu, Yongqian & Li, Qi, 2019. "A two-dimensional model based on the expansion of physical wake boundary for wind-turbine wakes," Applied Energy, Elsevier, vol. 233, pages 975-984.
    16. Lee, Jaejoon & Son, Eunkuk & Hwang, Byungho & Lee, Soogab, 2013. "Blade pitch angle control for aerodynamic performance optimization of a wind farm," Renewable Energy, Elsevier, vol. 54(C), pages 124-130.
    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. Dongqin Zhang & Yang Liang & Chao Li & Yiqing Xiao & Gang Hu, 2022. "Applicability of Wake Models to Predictions of Turbine-Induced Velocity Deficit and Wind Farm Power Generation," Energies, MDPI, vol. 15(19), pages 1-26, October.

    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. Zhang, Shaohai & Gao, Xiaoxia & Ma, Wanli & Lu, Hongkun & Lv, Tao & Xu, Shinai & Zhu, Xiaoxun & Sun, Haiying & Wang, Yu, 2023. "Derivation and verification of three-dimensional wake model of multiple wind turbines based on super-Gaussian function," Renewable Energy, Elsevier, vol. 215(C).
    2. 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).
    3. 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.
    4. Zhang, Shaohai & Duan, Huanfeng & Lu, Lin & He, Ruiyang & Gao, Xiaoxia & Zhu, Songye, 2024. "Quantification of three-dimensional added turbulence intensity for the horizontal-axis wind turbine considering the wake anisotropy," Energy, Elsevier, vol. 294(C).
    5. Zhang, Jincheng & Zhao, Xiaowei, 2020. "A novel dynamic wind farm wake model based on deep learning," Applied Energy, Elsevier, vol. 277(C).
    6. 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).
    7. Kuichao Ma & Huanqiang Zhang & Xiaoxia Gao & Xiaodong Wang & Heng Nian & Wei Fan, 2024. "Research on Evaluation Method of Wind Farm Wake Energy Efficiency Loss Based on SCADA Data Analysis," Sustainability, MDPI, vol. 16(5), pages 1-16, February.
    8. Ling, Ziyan & Zhao, Zhenzhou & Liu, Yige & Liu, Huiwen & Ali, Kashif & Liu, Yan & Wen, Yifan & Wang, Dingding & Li, Shijun & Su, Chunhao, 2024. "Multi-objective layout optimization for wind farms based on non-uniformly distributed turbulence and a new three-dimensional multiple wake model," Renewable Energy, Elsevier, vol. 227(C).
    9. He, Ruiyang & Yang, Hongxing & Sun, Haiying & Gao, Xiaoxia, 2021. "A novel three-dimensional wake model based on anisotropic Gaussian distribution for wind turbine wakes," Applied Energy, Elsevier, vol. 296(C).
    10. Gao, Xiaoxia & Zhang, Shaohai & Li, Luqing & Xu, Shinai & Chen, Yao & Zhu, Xiaoxun & Sun, Haiying & Wang, Yu & Lu, Hao, 2022. "Quantification of 3D spatiotemporal inhomogeneity for wake characteristics with validations from field measurement and wind tunnel test," Energy, Elsevier, vol. 254(PA).
    11. 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).
    12. 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.
    13. Wu, Chutian & Yang, Xiaolei & Zhu, Yaxin, 2021. "On the design of potential turbine positions for physics-informed optimization of wind farm layout," Renewable Energy, Elsevier, vol. 164(C), pages 1108-1120.
    14. 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.
    15. 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).
    16. 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).
    17. Tao, Siyu & Xu, Qingshan & Feijóo, Andrés & Zheng, Gang & Zhou, Jiemin, 2020. "Wind farm layout optimization with a three-dimensional Gaussian wake model," Renewable Energy, Elsevier, vol. 159(C), pages 553-569.
    18. Zhang, Ziyu & Huang, Peng, 2023. "Prediction of multiple-wake velocity and wind power using a cosine-shaped wake model," Renewable Energy, Elsevier, vol. 219(P1).
    19. Brogna, Roberto & Feng, Ju & Sørensen, Jens Nørkær & Shen, Wen Zhong & Porté-Agel, Fernando, 2020. "A new wake model and comparison of eight algorithms for layout optimization of wind farms in complex terrain," Applied Energy, Elsevier, vol. 259(C).
    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:185:y:2022:i:c:p:827-849. 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.