IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v326y2025ics0360544225019218.html

Aeroelastic stability analysis of large-scale wind turbine blades under different operating conditions based on system identification and Floquet theory

Author

Listed:
  • Wang, Yibo
  • Cai, Chang
  • Liao, Caicai
  • Hu, Zhiqiang
  • Zhang, Lei
  • Sun, Xiangyu
  • Zhong, Xiaohui
  • Li, Qing'an

Abstract

In recent years, the blade length of wind turbines has significantly increased, and the enhanced flexibility intensifies concerns about aeroelastic stability. Traditional time-frequency domain analysis methods necessitate the creation of simplified dynamics models and struggle to account for the time-varying periodicity of wind turbine blades during actual operation. To address these challenges, this paper establishes a linear time periodic system by a system identification method using the Particle Swarm Optimization (PSO) algorithm, and then conducts stability analysis based on Floquet theory. A commercial wind turbine with 78-m blades was selected for overall aeroelastic modeling, and time-domain stability analysis was conducted. The aeroelastic response signal was compared and verified for stability analysis using the improved linear periodic method. The linear time periodic system enables the analysis of multiple harmonics caused by periodicity, and the application of system identification technology significantly reduces the time required for stability judgment. This improved method was then used to analyze the aeroelastic stability of blades under varying operating conditions, including different wind speeds, pitch angles, and yaw conditions. The results demonstrated that the wind turbine blades are more prone to instability under high wind speed, low pitch angle, and low yaw angle conditions. This paper offers novel insights into the aeroelastic stability for large wind turbine blades considering the effect of periodicity, which provides practical application value for the optimization design and safe operation of large-scale wind turbine blades.

Suggested Citation

  • Wang, Yibo & Cai, Chang & Liao, Caicai & Hu, Zhiqiang & Zhang, Lei & Sun, Xiangyu & Zhong, Xiaohui & Li, Qing'an, 2025. "Aeroelastic stability analysis of large-scale wind turbine blades under different operating conditions based on system identification and Floquet theory," Energy, Elsevier, vol. 326(C).
  • Handle: RePEc:eee:energy:v:326:y:2025:i:c:s0360544225019218
    DOI: 10.1016/j.energy.2025.136279
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544225019218
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2025.136279?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Gao, Rongzhen & Yang, Junwei & Yang, Hua & Wang, Xiangjun, 2023. "Wind-tunnel experimental study on aeroelastic response of flexible wind turbine blades under different wind conditions," Renewable Energy, Elsevier, vol. 219(P2).
    2. Li, Xuyang & Qiu, Yingning & Feng, Yanhui & Wang, Zheng, 2021. "Wind turbine power prediction considering wake effects with dual laser beam LiDAR measured yaw misalignment," Applied Energy, Elsevier, vol. 299(C).
    3. Wang, Lin & Liu, Xiongwei & Renevier, Nathalie & Stables, Matthew & Hall, George M., 2014. "Nonlinear aeroelastic modelling for wind turbine blades based on blade element momentum theory and geometrically exact beam theory," Energy, Elsevier, vol. 76(C), pages 487-501.
    4. 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).
    5. Zheng, Jiancai & Wang, Nina & Wan, Decheng & Strijhak, Sergei, 2023. "Numerical investigations of coupled aeroelastic performance of wind turbines by elastic actuator line model," Applied Energy, Elsevier, vol. 330(PB).
    6. Delgarm, N. & Sajadi, B. & Kowsary, F. & Delgarm, S., 2016. "Multi-objective optimization of the building energy performance: A simulation-based approach by means of particle swarm optimization (PSO)," Applied Energy, Elsevier, vol. 170(C), pages 293-303.
    7. 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).
    8. Qian, Jing & Sun, Xiangyu & Zhong, Xiaohui & Zeng, Jiajun & Xu, Fei & Zhou, Teng & Shi, Kezhong & Li, Qingan, 2024. "Multi-objective optimization design of the wind-to-heat system blades based on the Particle Swarm Optimization algorithm," Applied Energy, Elsevier, vol. 355(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. Lapa, Gabriel Vicentin Pereira & Gay Neto, Alfredo & Franzini, Guilherme Rosa, 2023. "Effects of blade torsion on IEA 15MW turbine rotor operation," Renewable Energy, Elsevier, vol. 219(P2).
    11. Xu, Jin & Zhang, Lei & Li, Xue & Li, Shuang & Yang, Ke, 2020. "A study of dynamic response of a wind turbine blade based on the multi-body dynamics method," Renewable Energy, Elsevier, vol. 155(C), pages 358-368.
    12. Zuo, Haoran & Bi, Kaiming & Hao, Hong, 2020. "A state-of-the-art review on the vibration mitigation of wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 121(C).
    13. Liu, Xiong & Lu, Cheng & Liang, Shi & Godbole, Ajit & Chen, Yan, 2017. "Vibration-induced aerodynamic loads on large horizontal axis wind turbine blades," Applied Energy, Elsevier, vol. 185(P2), pages 1109-1119.
    14. 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.
    15. Wang, Lu & Bergua, Roger & Robertson, Amy & Wright, Alan & Zalkind, Daniel & Fowler, Matthew & Lenfest, Eben & Viselli, Anthony & Goupee, Andrew & Kimball, Richard, 2024. "Experimental investigation of advanced turbine control strategies and load-mitigation measures with a model-scale floating offshore wind turbine system," Applied Energy, Elsevier, vol. 355(C).
    16. Hui, Yi & Jiang, Bowen & Yang, Qingshan & Law, Siu-seong, 2024. "Continuum approach of nonlinear dynamic analysis of a rotating wind turbine blade considering hub motion," Renewable Energy, Elsevier, vol. 231(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. Xiangqian Zhu & Siming Yang & Zhiqiang Yang & Chang Cai & Lei Zhang & Qing’an Li & Jin-Hwan Choi, 2025. "Structure/Aerodynamic Nonlinear Dynamic Simulation Analysis of Long, Flexible Blade of Wind Turbine," Energies, MDPI, vol. 18(16), pages 1-21, August.

    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. Wang, Zedong & Hu, Jianjian & Wang, Yu & Yang, Mindong & Zhou, Binzhen & Yuan, Yuming & Jin, Peng & Chen, Yan, 2026. "Nonlinear aeroelastic performance in 5 MW and 15 MW wind turbine blades using intrinsic geometrically exact method," Renewable Energy, Elsevier, vol. 256(PI).
    2. Wang, Zedong & Hu, Jianjian & Wang, Yu & Zhang, Yuanyuan & Zhou, Binzhen & Jin, Peng & Qi, Liangwen & Chen, Yan, 2025. "Nonlinear dynamic response of long flexible wind turbine blades based on intrinsic geometrically exact theory," Energy, Elsevier, vol. 338(C).
    3. Lapa, Gabriel Vicentin Pereira & Gay Neto, Alfredo & Franzini, Guilherme Rosa, 2023. "Effects of blade torsion on IEA 15MW turbine rotor operation," Renewable Energy, Elsevier, vol. 219(P2).
    4. Shine Win Naung & Mohammad Rahmati & Htet Shine, 2025. "High-Fidelity Aeroelastic Analysis of a Wind Turbine Using a Nonlinear Frequency-Domain Solution Method," Energies, MDPI, vol. 18(5), pages 1-20, February.
    5. 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.
    6. 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.
    7. Mo, Shuai & Liu, Yiheng & Zhang, Yingxin & Zhou, Yuansheng & Huang, Yurong & Houjoh, Haruo & Zhang, Wei, 2025. "Nonlinear dynamics of wind power transmission system with blades," Renewable Energy, Elsevier, vol. 249(C).
    8. Zhou, Le & Shen, Xin & Ma, Lu & Ouyang, Hua & Du, Zhaohui, 2025. "Unsteady aeroelastic performance of the 15 MW floating offshore wind turbine under surge condition," Energy, Elsevier, vol. 336(C).
    9. Liu, Songyang & Xin, Zhiqiang & Wang, Lei & Xu, Yanming & Cai, Zhiming, 2025. "Fluid–structure interaction simulation of the effect of static yaw control on the aerodynamic responses and wake characteristics of floating offshore wind turbines," Energy, Elsevier, vol. 330(C).
    10. 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.
    11. Huang, Wei & Tang, Rongjiang & Ma, Huihuan, 2024. "The review of Vortex lattice method for offshore wind turbines," Renewable Energy, Elsevier, vol. 236(C).
    12. Haojie Kang & Bofeng Xu & Xiang Shen & Zhen Li & Xin Cai & Zhiqiang Hu, 2023. "Comparison of Blade Aeroelastic Responses between Upwind and Downwind of 10 MW Wind Turbines under the Shear Wind Condition," Energies, MDPI, vol. 16(6), pages 1-13, March.
    13. Liu, Xiong & Lu, Cheng & Li, Gangqiang & Godbole, Ajit & Chen, Yan, 2017. "Effects of aerodynamic damping on the tower load of offshore horizontal axis wind turbines," Applied Energy, Elsevier, vol. 204(C), pages 1101-1114.
    14. Xiangqian Zhu & Siming Yang & Zhiqiang Yang & Chang Cai & Lei Zhang & Qing’an Li & Jin-Hwan Choi, 2025. "Structure/Aerodynamic Nonlinear Dynamic Simulation Analysis of Long, Flexible Blade of Wind Turbine," Energies, MDPI, vol. 18(16), pages 1-21, August.
    15. Tu, Yu & Chen, Yaoran & Zhang, Kai & He, Ruiyang & Han, Zhaolong & Zhou, Dai, 2025. "A multi-fidelity framework for power prediction of wind farm under yaw misalignment," Applied Energy, Elsevier, vol. 377(PC).
    16. Gao, Rongzhen & Yang, Junwei & Yang, Hua & Wang, Xiangjun, 2023. "Wind-tunnel experimental study on aeroelastic response of flexible wind turbine blades under different wind conditions," Renewable Energy, Elsevier, vol. 219(P2).
    17. 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.
    18. Wang, Xiangjun & Jiang, Lifeng & Amjad, Ali & Yang, Hua & Yang, Junwei, 2024. "Experimental investigation on Aeroelastic response of long flexible blades in turbulent flow," Applied Energy, Elsevier, vol. 375(C).
    19. Zhou, J.W. & Zhang, W. & Jiang, X. & Zhai, E.D., 2022. "Investigation on dynamics of rotating wind turbine blade using transferred differential transformation method," Renewable Energy, Elsevier, vol. 188(C), pages 96-113.
    20. 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.

    More about this item

    Statistics

    Access and download statistics

    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:326:y:2025:i:c:s0360544225019218. 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.