IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i20p4012-d279062.html
   My bibliography  Save this article

A New Method of Determination of the Angle of Attack on Rotating Wind Turbine Blades

Author

Listed:
  • Wei Zhong

    (Jiangsu Key Laboratory of Hi-Tech Research for Wind Turbine Design, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Wen Zhong Shen

    (Department of Wind Energy, Technical University of Denmark, 2800 Lyngby, Denmark)

  • Tong Guang Wang

    (Jiangsu Key Laboratory of Hi-Tech Research for Wind Turbine Design, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Wei Jun Zhu

    (School of Hydraulic Energy and Power Engineering, Yangzhou University, Yangzhou 225009, China)

Abstract

The angle of attack (AoA) is the key parameter when extracting the aerodynamic polar from the rotating blade sections of a wind turbine. However, the determination of AoA is not straightforward using computational fluid dynamics (CFD) or measurement. Since the incoming streamlines are bent because of the complex inductions of the rotor, discrepancies exist between various existing determination methods, especially in the tip region. In the present study, flow characteristics in the region near wind turbine blades are analyzed in detail using CFD results of flows past the NREL UAE Phase VI rotor. It is found that the local flow determining AOA changes rapidly in the vicinity of the blade. Based on this finding, the concepts of effective AoA as well as nominal AoA are introduced, leading to a new method of AOA determination. The new method has 5 steps: (1) Find the distributed vortices on the blade surface; (2) select two monitoring points per cross-section close to the aerodynamic center on both pressure and suction sides with an equal distance from the rotor plane; (3) subtract the blade self-induction from the velocity at each monitoring point; (4) average the velocity of the two monitoring points obtained in Step 3; (5) determine the AoA using the velocity obtained in Step 4. Since the monitoring points for the first time can be set very close to the aerodynamic center, leading to an excellent estimation of AoA. The aerodynamic polar extracted through determination of the effective AoA exhibits a consistent regularity for both the mid-board and tip sections, which has never been obtained by the existing determination methods.

Suggested Citation

  • Wei Zhong & Wen Zhong Shen & Tong Guang Wang & Wei Jun Zhu, 2019. "A New Method of Determination of the Angle of Attack on Rotating Wind Turbine Blades," Energies, MDPI, vol. 12(20), pages 1-19, October.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:20:p:4012-:d:279062
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/20/4012/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/20/4012/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wen, Binrong & Tian, Xinliang & Dong, Xingjian & Peng, Zhike & Zhang, Wenming & Wei, Kexiang, 2019. "A numerical study on the angle of attack to the blade of a horizontal-axis offshore floating wind turbine under static and dynamic yawed conditions," Energy, Elsevier, vol. 168(C), pages 1138-1156.
    2. Rahimi, H. & Schepers, J.G. & Shen, W.Z. & García, N. Ramos & Schneider, M.S. & Micallef, D. & Ferreira, C.J. Simao & Jost, E. & Klein, L. & Herráez, I., 2018. "Evaluation of different methods for determining the angle of attack on wind turbine blades with CFD results under axial inflow conditions," Renewable Energy, Elsevier, vol. 125(C), pages 866-876.
    3. Bai, Chi-Jeng & Wang, Wei-Cheng, 2016. "Review of computational and experimental approaches to analysis of aerodynamic performance in horizontal-axis wind turbines (HAWTs)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 63(C), pages 506-519.
    4. Jonathon Sumner & Christophe Sibuet Watters & Christian Masson, 2010. "CFD in Wind Energy: The Virtual, Multiscale Wind Tunnel," Energies, MDPI, vol. 3(5), pages 1-25, May.
    5. Moutaz Elgammi & Tonio Sant, 2016. "Combining Unsteady Blade Pressure Measurements and a Free-Wake Vortex Model to Investigate the Cycle-to-Cycle Variations in Wind Turbine Aerodynamic Blade Loads in Yaw," Energies, MDPI, vol. 9(6), pages 1-27, June.
    6. Chengyong Zhu & Tongguang Wang & Wei Zhong, 2019. "Combined Effect of Rotational Augmentation and Dynamic Stall on a Horizontal Axis Wind Turbine," Energies, MDPI, vol. 12(8), pages 1-20, April.
    7. Syed Ahmed Kabir, Ijaz Fazil & Ng, E.Y.K., 2017. "Insight into stall delay and computation of 3D sectional aerofoil characteristics of NREL phase VI wind turbine using inverse BEM and improvement in BEM analysis accounting for stall delay effect," Energy, Elsevier, vol. 120(C), pages 518-536.
    8. Shaler, Kelsey & Kecskemety, Krista M. & McNamara, Jack J., 2019. "Benchmarking of a Free Vortex Wake Model for Prediction of Wake Interactions," Renewable Energy, Elsevier, vol. 136(C), pages 607-620.
    9. Zhong, W. & Shen, W.Z. & Wang, T. & Li, Y., 2020. "A tip loss correction model for wind turbine aerodynamic performance prediction," Renewable Energy, Elsevier, vol. 147(P1), pages 223-238.
    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. Boatto, Umberto & Bonnet, Paul A. & Avallone, Francesco & Ragni, Daniele, 2023. "Assessment of Blade Element Momentum Theory-based engineering models for wind turbine rotors under uniform steady inflow," Renewable Energy, Elsevier, vol. 214(C), pages 307-317.
    2. 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.
    3. Mohammadi, Morteza & Maghrebi, Mohammad Javad, 2021. "Improvement of wind turbine aerodynamic performance by vanquishing stall with active multi air jet blowing," Energy, Elsevier, vol. 224(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. Xiaodong Wang & Zhaoliang Ye & Shun Kang & Hui Hu, 2019. "Investigations on the Unsteady Aerodynamic Characteristics of a Horizontal-Axis Wind Turbine during Dynamic Yaw Processes," Energies, MDPI, vol. 12(16), pages 1-23, August.
    2. Thé, Jesse & Yu, Hesheng, 2017. "A critical review on the simulations of wind turbine aerodynamics focusing on hybrid RANS-LES methods," Energy, Elsevier, vol. 138(C), pages 257-289.
    3. Zhong, Junwei & Li, Jingyin, 2020. "Aerodynamic performance prediction of NREL phase VI blade adopting biplane airfoil," Energy, Elsevier, vol. 206(C).
    4. 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).
    5. Boatto, Umberto & Bonnet, Paul A. & Avallone, Francesco & Ragni, Daniele, 2023. "Assessment of Blade Element Momentum Theory-based engineering models for wind turbine rotors under uniform steady inflow," Renewable Energy, Elsevier, vol. 214(C), pages 307-317.
    6. Amiri, Mojtaba Maali & Shadman, Milad & Estefen, Segen F., 2020. "URANS simulations of a horizontal axis wind turbine under stall condition using Reynolds stress turbulence models," Energy, Elsevier, vol. 213(C).
    7. Wenyan Li & Yuxuan Xiong & Guoliang Su & Zuyang Ye & Guowu Wang & Zhao Chen, 2023. "The Aerodynamic Performance of Horizontal Axis Wind Turbines under Rotation Condition," Sustainability, MDPI, vol. 15(16), pages 1-15, August.
    8. Ali, Qazi Shahzad & Kim, Man-Hoe, 2022. "Power conversion performance of airborne wind turbine under unsteady loads," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    9. Zhu, Chengyong & Qiu, Yingning & Wang, Tongguang, 2021. "Dynamic stall of the wind turbine airfoil and blade undergoing pitch oscillations: A comparative study," Energy, Elsevier, vol. 222(C).
    10. Eid Gul & Giorgio Baldinelli & Pietro Bartocci, 2022. "Energy Transition: Renewable Energy-Based Combined Heat and Power Optimization Model for Distributed Communities," Energies, MDPI, vol. 15(18), pages 1-18, September.
    11. Wang, Peilin & Liu, Qingsong & Li, Chun & Miao, Weipao & Yue, Minnan & Xu, Zifei, 2022. "Investigation of the aerodynamic characteristics of horizontal axis wind turbine using an active flow control method via boundary layer suction," Renewable Energy, Elsevier, vol. 198(C), pages 1032-1048.
    12. Guo, Yize & Wang, Xiaodong & Mei, Yuanhang & Ye, Zhaoliang & Guo, Xiaojiang, 2022. "Effect of coupled platform pitch-surge motions on the aerodynamic characters of a horizontal floating offshore wind turbine," Renewable Energy, Elsevier, vol. 196(C), pages 278-297.
    13. Albara M. Mustafa & Abbas Barabadi, 2022. "Criteria-Based Fuzzy Logic Risk Analysis of Wind Farms Operation in Cold Climate Regions," Energies, MDPI, vol. 15(4), pages 1-17, February.
    14. 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).
    15. Fan Zhang & Juchuan Dai & Deshun Liu & Linxing Li & Xin Long, 2019. "Investigation of the Pitch Load of Large-Scale Wind Turbines Using Field SCADA Data," Energies, MDPI, vol. 12(3), pages 1-20, February.
    16. Elgammi, Moutaz & Sant, Tonio & Alshaikh, Moftah, 2020. "Predicting the stochastic aerodynamic loads on blades of two yawed downwind hawts in uncontrolled conditions using a bem algorithm," Renewable Energy, Elsevier, vol. 146(C), pages 371-383.
    17. Romanic, Djordje & Parvu, Dan & Refan, Maryam & Hangan, Horia, 2018. "Wind and tornado climatologies and wind resource modelling for a modern development situated in “Tornado Alley”," Renewable Energy, Elsevier, vol. 115(C), pages 97-112.
    18. Hussein A. Mahmood & Nor Mariah. Adam & B. B. Sahari & S. U. Masuri, 2017. "New Design of a CNG-H 2 -AIR Mixer for Internal Combustion Engines: An Experimental and Numerical Study," Energies, MDPI, vol. 10(9), pages 1-27, September.
    19. Shaohui Li & Xuejin Sun & Riwei Zhang & Chuanliang Zhang, 2019. "A Feasibility Study of Simulating the Micro-Scale Wind Field for Wind Energy Applications by NWP/CFD Model with Improved Coupling Method and Data Assimilation," Energies, MDPI, vol. 12(13), pages 1-19, July.
    20. 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.

    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:12:y:2019:i:20:p:4012-:d:279062. 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.