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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

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  • Syed Ahmed Kabir, Ijaz Fazil
  • Ng, E.Y.K.

Abstract

In this paper, analysis of stall delay phenomenon for the NREL Phase VI wind turbine is done in order to improve Blade Element Momentum (BEM) method. The current study includes different proposals for extrapolation of 2D aerofoil characteristics for S809 aerofoil at higher angles of attack and their implementation in BEM analysis and comparison with experiment results. Also four existing stall delay corrections models are examined. In general BEM with no stall delay models did not account for stall delay and BEM with existing stall delay models result in over-prediction of lift coefficients at inboard sections of the blade at higher wind speed. Improved inverse BEM method is developed here to compute 3D aerofoil characteristics. In addition to five radial locations as described in the NREL/NASA Ames test analysis, thirteen additional radial locations are considered for a better understanding of stall delay. A new BEM model with the local radius effect for aerofoil characteristics (other than as a function of Reynolds number and angle of attack only) is proposed. Implementation of the new model showed a good agreement with aerofoil characteristics distribution along the blade span. It further revealed a good matching for overall thrust comparison and promising comparison in power computation.

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  • 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.
    • Handle: RePEc:eee:energy:v:120:y:2017:i:c:p:518-536
    DOI: 10.1016/j.energy.2016.11.102
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    References listed on IDEAS

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    Cited by:

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    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. 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.
    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. Abdelsalam, Ali M. & El-Askary, W.A. & Kotb, M.A. & Sakr, I.M., 2021. "Experimental study on small scale horizontal axis wind turbine of analytically-optimized blade with linearized chord twist angle profile," Energy, Elsevier, vol. 216(C).
    6. 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.
    7. 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.
    8. Shantanu Purohit & Ijaz Fazil Syed Ahmed Kabir & E. Y. K. Ng, 2021. "On the Accuracy of uRANS and LES-Based CFD Modeling Approaches for Rotor and Wake Aerodynamics of the (New) MEXICO Wind Turbine Rotor Phase-III," Energies, MDPI, vol. 14(16), pages 1-26, August.
    9. 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.
    10. Hamlaoui, M.N. & Smaili, A. & Dobrev, I. & Pereira, M. & Fellouah, H. & Khelladi, S., 2022. "Numerical and experimental investigations of HAWT near wake predictions using Particle Image Velocimetry and Actuator Disk Method," Energy, Elsevier, vol. 238(PB).
    11. Zhong, Junwei & Li, Jingyin, 2020. "Aerodynamic performance prediction of NREL phase VI blade adopting biplane airfoil," Energy, Elsevier, vol. 206(C).
    12. Sun, ZhaoCheng & Li, Dong & Mao, YuFeng & Feng, Long & Zhang, Yue & Liu, Chao, 2022. "Anti-cavitation optimal design and experimental research on tidal turbines based on improved inverse BEM," Energy, Elsevier, vol. 239(PD).

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