IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v249y2022ics0360544222005734.html
   My bibliography  Save this article

CFD simulations of aerodynamic characteristics for the three-blade NREL Phase VI wind turbine model

Author

Listed:
  • Ji, Baifeng
  • Zhong, Kuanwei
  • Xiong, Qian
  • Qiu, Penghui
  • Zhang, Xu
  • Wang, Liang

Abstract

In order to study the impact of the wind speed and turbulence model on the numerical simulation of the aerodynamic characteristics for the wind turbine, SST k–ω and transition SST turbulence models were used to numerically simulate the aerodynamic characteristics at 7 m/s, 10 m/s and 20 m/s inlet wind speed, and the numerical results were compared with the experimental results. The results show that as the low inlet wind speed, no flow separation occurs over most of the blade surface, and SST k–ω and transition SST turbulence models can accurately predict the aerodynamic characteristics of the blades. As the low inlet wind speed, the flow separation mainly occurs around the root and the middle of blade, and numerical results at the leading edge by SST k-ω turbulence model and near the trailing edge by transition SST turbulence model match the experimental results well. When most of the flow through the blade surface is completely separated, the numerical simulation results by both SST k–ω and transition SST turbulence models have certain differences with experiment results, and the deviations are mainly concentrated on the suction surface and decrease gradually from the blade root to the tip.

Suggested Citation

  • Ji, Baifeng & Zhong, Kuanwei & Xiong, Qian & Qiu, Penghui & Zhang, Xu & Wang, Liang, 2022. "CFD simulations of aerodynamic characteristics for the three-blade NREL Phase VI wind turbine model," Energy, Elsevier, vol. 249(C).
    • Handle: RePEc:eee:energy:v:249:y:2022:i:c:s0360544222005734
    DOI: 10.1016/j.energy.2022.123670
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222005734
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2022.123670?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. Yayla, Sedat & Ayça, Sümeyya & Oruç, Mehmet, 2020. "A case study on piezoelectric energy harvesting with using vortex generator plate modeling for fluids," Renewable Energy, Elsevier, vol. 157(C), pages 1243-1253.
    2. Lanzafame, R. & Mauro, S. & Messina, M., 2013. "Wind turbine CFD modeling using a correlation-based transitional model," Renewable Energy, Elsevier, vol. 52(C), pages 31-39.
    3. Kyoungsoo Lee & Shrabanti Roy & Ziaul Huque & Raghava Kommalapati & SangEul Han, 2017. "Effect on Torque and Thrust of the Pointed Tip Shape of a Wind Turbine Blade," Energies, MDPI, vol. 10(1), pages 1-20, January.
    4. Syed Ahmed Kabir, Ijaz Fazil & Ng, E.Y.K., 2019. "Effect of different atmospheric boundary layers on the wake characteristics of NREL phase VI wind turbine," Renewable Energy, Elsevier, vol. 130(C), pages 1185-1197.
    5. Mustafa Kaya, 2019. "A CFD Based Application of Support Vector Regression to Determine the Optimum Smooth Twist for Wind Turbine Blades," Sustainability, MDPI, vol. 11(16), pages 1-25, August.
    6. Zhu, Chengyong & Chen, Jie & Qiu, Yingning & Wang, Tongguang, 2021. "Numerical investigation into rotational augmentation with passive vortex generators on the NREL Phase VI blade," Energy, Elsevier, vol. 223(C).
    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. Xu, Changwei & Nie, Wen & Peng, Huitian & Zhang, Shaobo & Liu, Fei & Yi, Shixing & Cha, Xingpeng & Mwabaima, Felicie Ilele, 2023. "Numerical simulation of the dynamic wetting of coal dust by spray droplets," Energy, Elsevier, vol. 270(C).
    2. Zhang, Zhihao & Kuang, Limin & Han, Zhaolong & Zhou, Dai & Zhao, Yongsheng & Bao, Yan & Duan, Lei & Tu, Jiahuang & Chen, Yaoran & Chen, Mingsheng, 2023. "Comparative analysis of bent and basic winglets on performance improvement of horizontal axis wind turbines," Energy, Elsevier, vol. 281(C).
    3. Hércules Araújo Oliveira & José Gomes de Matos & Luiz Antonio de Souza Ribeiro & Osvaldo Ronald Saavedra & Jerson Rogério Pinheiro Vaz, 2023. "Assessment of Correction Methods Applied to BEMT for Predicting Performance of Horizontal-Axis Wind Turbines," Sustainability, MDPI, vol. 15(8), pages 1-26, April.
    4. Dao, My Ha & Le, Quang Tuyen & Zhao, Xiang & Ooi, Chin Chun & Duong, Luu Trung Pham & Raghavan, Nagarajan, 2024. "Modelling of aero-mechanical response of wind turbine blade with damages by computational fluid dynamics, finite element analysis and Bayesian network," Renewable Energy, Elsevier, vol. 227(C).
    5. Zhang, Dongqin & Liu, Zhenqing & Li, Weipeng & Hu, Gang, 2023. "LES simulation study of wind turbine aerodynamic characteristics with fluid-structure interaction analysis considering blade and tower flexibility," Energy, Elsevier, vol. 282(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. Zhang, Dongqin & Liu, Zhenqing & Li, Weipeng & Hu, Gang, 2023. "LES simulation study of wind turbine aerodynamic characteristics with fluid-structure interaction analysis considering blade and tower flexibility," Energy, Elsevier, vol. 282(C).
    2. Mauro, S. & Lanzafame, R. & Messina, M. & Brusca, S., 2023. "On the importance of the root-to-hub adapter effects on HAWT performance: A CFD-BEM numerical investigation," Energy, Elsevier, vol. 275(C).
    3. N. Aravindhan & M. P. Natarajan & S. Ponnuvel & P.K. Devan, 2023. "Recent developments and issues of small-scale wind turbines in urban residential buildings- A review," Energy & Environment, , vol. 34(4), pages 1142-1169, June.
    4. Jinghua Lin & You-Lin Xu & Yong Xia & Chao Li, 2019. "Structural Analysis of Large-Scale Vertical-Axis Wind Turbines, Part I: Wind Load Simulation," Energies, MDPI, vol. 12(13), pages 1-31, July.
    5. Lee, Kyoungsoo & Huque, Ziaul & Kommalapati, Raghava & Han, Sang-Eul, 2016. "Evaluation of equivalent structural properties of NREL phase VI wind turbine blade," Renewable Energy, Elsevier, vol. 86(C), pages 796-818.
    6. Qian, Feng & Liu, Mingyi & Huang, Jianuo & Zhang, Jiajun & Jung, Hyunjun & Deng, Zhiqun Daniel & Hajj, Muhammad R. & Zuo, Lei, 2022. "Bio-inspired bistable piezoelectric energy harvester for powering animal telemetry tags: Conceptual design and preliminary experimental validation," Renewable Energy, Elsevier, vol. 187(C), pages 34-43.
    7. Xiao, Han & Liu, Zhenwei & Zhang, Ran & Kelham, Andrew & Xu, Xiangyang & Wang, Xu, 2021. "Study of a novel rotational speed amplified dual turbine wheel wave energy converter," Applied Energy, Elsevier, vol. 301(C).
    8. Ebrahimi, Abbas & Movahhedi, Mohammadreza, 2018. "Wind turbine power improvement utilizing passive flow control with microtab," Energy, Elsevier, vol. 150(C), pages 575-582.
    9. Mauro, S. & Brusca, S. & Lanzafame, R. & Messina, M., 2019. "CFD modeling of a ducted Savonius wind turbine for the evaluation of the blockage effects on rotor performance," Renewable Energy, Elsevier, vol. 141(C), pages 28-39.
    10. Wang, Jian-Xu & Su, Wen-Bin & Li, Ji-Chao & Wang, Chun-Ming, 2022. "A rotational piezoelectric energy harvester based on trapezoid beam: Simulation and experiment," Renewable Energy, Elsevier, vol. 184(C), pages 619-626.
    11. 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.
    12. Purohit, Shantanu & Ng, E.Y.K. & Syed Ahmed Kabir, Ijaz Fazil, 2022. "Evaluation of three potential machine learning algorithms for predicting the velocity and turbulence intensity of a wind turbine wake," Renewable Energy, Elsevier, vol. 184(C), pages 405-420.
    13. Miller, Aaron & Chang, Byungik & Issa, Roy & Chen, Gerald, 2013. "Review of computer-aided numerical simulation in wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 122-134.
    14. Liu, Pengyin & Yu, Guohua & Zhu, Xiaocheng & Du, Zhaohui, 2014. "Unsteady aerodynamic prediction for dynamic stall of wind turbine airfoils with the reduced order modeling," Renewable Energy, Elsevier, vol. 69(C), pages 402-409.
    15. Kiran Siddappaji & Mark Turner, 2022. "Improved Prediction of Aerodynamic Loss Propagation as Entropy Rise in Wind Turbines Using Multifidelity Analysis," Energies, MDPI, vol. 15(11), pages 1-44, May.
    16. Ali, Qazi Shahzad & Kim, Man-Hoe, 2021. "Design and performance analysis of an airborne wind turbine for high-altitude energy harvesting," Energy, Elsevier, vol. 230(C).
    17. Cheng, Biyi & Yao, Yingxue, 2023. "Machine learning based surrogate model to analyze wind tunnel experiment data of Darrieus wind turbines," Energy, Elsevier, vol. 278(PA).
    18. Pérez Albornoz, C. & Escalante Soberanis, M.A. & Ramírez Rivera, V. & Rivero, M., 2022. "Review of atmospheric stability estimations for wind power applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    19. Akhter, Md Zishan & Ali, Ahmed Riyadh & Jawahar, Hasan Kamliya & Omar, Farag Khalifa & Elnajjar, Emad, 2023. "Performance enhancement of small-scale wind turbine featuring morphing blades," Energy, Elsevier, vol. 278(C).
    20. Jiang, Ruifang & Zhao, Zhenzhou & Liu, Huiwen & Wang, Tongguang & Chen, Ming & Feng, Junxin & Wang, Dingding, 2022. "Numerical study on the influence of vortex generators on wind turbine aerodynamic performance considering rotational effect," Renewable Energy, Elsevier, vol. 186(C), pages 730-741.

    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:249:y:2022:i:c:s0360544222005734. 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.