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The impact of yaw error on aeroelastic characteristics of a horizontal axis wind turbine blade

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  • Jeong, Min-Soo
  • Kim, Sang-Woo
  • Lee, In
  • Yoo, Seung-Jae
  • Park, K.C.

Abstract

Horizontal axis wind turbines operate under yawed conditions for a considerable period of time due to the power control mechanism or sudden changes in the wind direction. This in turn can alter the dynamic characteristics of a turbine blade because the flow over the rotor plane may trigger complicated induced velocity patterns. In this study, an aeroelastic analysis under yawed flow conditions is carried out to investigate the effects of yaw error on the blade behaviors and dynamic stability. A beam model including geometric nonlinearity coupled with unsteady aerodynamics based on a free-vortex wake method with the blade element theory is employed in the present study. The aerodynamic approach for a horizontal axis wind turbine blade under yawed flow conditions is verified through comparison with measurements. It is also shown that the present method gives slightly better results at high yaw angles than does the method previously published in the literature. The dynamic instabilities of a National Renewable Energy Laboratory 5 MW reference wind turbine have subsequently been investigated for various wind speeds and yaw angles. Observations are made that yaw effects induce considerable changes in airloads and blade structural behavior. Also, the aeroelastic damping values for this particular blade under yawed flow conditions can be reduced by up to approximately 33% in the worst case. Therefore, it is concluded that the impacts of yaw misalignments adversely influenced the dynamic aeroelastic stability of the horizontal axis wind turbine blade.

Suggested Citation

  • Jeong, Min-Soo & Kim, Sang-Woo & Lee, In & Yoo, Seung-Jae & Park, K.C., 2013. "The impact of yaw error on aeroelastic characteristics of a horizontal axis wind turbine blade," Renewable Energy, Elsevier, vol. 60(C), pages 256-268.
    • Handle: RePEc:eee:renene:v:60:y:2013:i:c:p:256-268
    DOI: 10.1016/j.renene.2013.05.014
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    References listed on IDEAS

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    1. Shen, Xin & Zhu, Xiaocheng & Du, Zhaohui, 2011. "Wind turbine aerodynamics and loads control in wind shear flow," Energy, Elsevier, vol. 36(3), pages 1424-1434.
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    1. Ebrahimi, Abbas & Sekandari, Mahmood, 2018. "Transient response of the flexible blade of horizontal-axis wind turbines in wind gusts and rapid yaw changes," Energy, Elsevier, vol. 145(C), pages 261-275.
    2. Dai, Juchuan & Yang, Xin & Hu, Wei & Wen, Li & Tan, Yayi, 2018. "Effect investigation of yaw on wind turbine performance based on SCADA data," Energy, Elsevier, vol. 149(C), pages 684-696.
    3. Davide Astolfi & Francesco Castellani & Matteo Becchetti & Andrea Lombardi & Ludovico Terzi, 2020. "Wind Turbine Systematic Yaw Error: Operation Data Analysis Techniques for Detecting It and Assessing Its Performance Impact," Energies, MDPI, vol. 13(9), pages 1-17, May.
    4. Win Naung, Shine & Nakhchi, Mahdi Erfanian & Rahmati, Mohammad, 2021. "High-fidelity CFD simulations of two wind turbines in arrays using nonlinear frequency domain solution method," Renewable Energy, Elsevier, vol. 174(C), pages 984-1005.
    5. Qiu, Yong-Xing & Wang, Xiao-Dong & Kang, Shun & Zhao, Ming & Liang, Jun-Yu, 2014. "Predictions of unsteady HAWT aerodynamics in yawing and pitching using the free vortex method," Renewable Energy, Elsevier, vol. 70(C), pages 93-106.
    6. Ke, Shitang & Yu, Wenlin & Wang, Tongguang & Ge, Yaojun, 2019. "Aerodynamic performance and wind-induced effect of large-scale wind turbine system under yaw and wind-rain combination action," Renewable Energy, Elsevier, vol. 136(C), pages 235-253.
    7. Shuting Wan & Lifeng Cheng & Xiaoling Sheng, 2015. "Effects of Yaw Error on Wind Turbine Running Characteristics Based on the Equivalent Wind Speed Model," Energies, MDPI, vol. 8(7), pages 1-16, June.
    8. Wu, Guangxing & Zhang, Chaoyu & Cai, Chang & Yang, Ke & Shi, Kezhong, 2020. "Uncertainty prediction on the angle of attack of wind turbine blades based on the field measurements," Energy, Elsevier, vol. 200(C).
    9. Wang, Lin & Liu, Xiongwei & Kolios, Athanasios, 2016. "State of the art in the aeroelasticity of wind turbine blades: Aeroelastic modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 195-210.
    10. Yang, Jian & Wang, Li & Song, Dongran & Huang, Chaoneng & Huang, Liansheng & Wang, Junlei, 2022. "Incorporating environmental impacts into zero-point shifting diagnosis of wind turbines yaw angle," Energy, Elsevier, vol. 238(PA).
    11. Weimin Wu & Xiongfei Liu & Jingcheng Liu & Shunpeng Zeng & Chuande Zhou & Xiaomei Wang, 2021. "Investigation into Yaw Motion Influence of Horizontal-Axis Wind Turbine on Wake Flow Using LBM-LES," Energies, MDPI, vol. 14(17), pages 1-37, August.
    12. Jing, Bo & Qian, Zheng & Pei, Yan & Zhang, Lizhong & Yang, Tingyi, 2020. "Improving wind turbine efficiency through detection and calibration of yaw misalignment," Renewable Energy, Elsevier, vol. 160(C), pages 1217-1227.
    13. 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.
    14. Win Naung, Shine & Rahmati, Mohammad & Farokhi, Hamed, 2021. "Nonlinear frequency domain solution method for aerodynamic and aeromechanical analysis of wind turbines," Renewable Energy, Elsevier, vol. 167(C), pages 66-81.
    15. Yan Pei & Zheng Qian & Bo Jing & Dahai Kang & Lizhong Zhang, 2018. "Data-Driven Method for Wind Turbine Yaw Angle Sensor Zero-Point Shifting Fault Detection," Energies, MDPI, vol. 11(3), pages 1-14, March.
    16. He, Ruiyang & Yang, Hongxing & Lu, Lin, 2023. "Optimal yaw strategy and fatigue analysis of wind turbines under the combined effects of wake and yaw control," Applied Energy, Elsevier, vol. 337(C).
    17. Škvorc, Petar & Kozmar, Hrvoje, 2021. "Wind energy harnessing on tall buildings in urban environments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    18. Davide Astolfi & Ravi Pandit & Linyue Gao & Jiarong Hong, 2022. "Individuation of Wind Turbine Systematic Yaw Error through SCADA Data," Energies, MDPI, vol. 15(21), pages 1-5, November.
    19. Jeong, Min-Soo & Cha, Myung-Chan & Kim, Sang-Woo & Lee, In, 2015. "Numerical investigation of optimal yaw misalignment and collective pitch angle for load imbalance reduction of rigid and flexible HAWT blades under sheared inflow," Energy, Elsevier, vol. 84(C), pages 518-532.
    20. Dai, Juchuan & He, Tao & Li, Mimi & Long, Xin, 2021. "Performance study of multi-source driving yaw system for aiding yaw control of wind turbines," Renewable Energy, Elsevier, vol. 163(C), pages 154-171.
    21. 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.

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