IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i19p5290-d1765764.html

Fatigue Load Analysis of Yawed Wind Turbines Considering Geometric Nonlinearity of Blades

Author

Listed:
  • Dereje Haile Hirgeto

    (State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University, Shanghai 200092, China)

  • Guo-Wei Qian

    (Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), School of Ocean Engineering and Technology, Sun Yat-sen University, Zhuhai 519082, China)

  • Xuan-Yi Zhou

    (State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University, Shanghai 200092, China)

  • Wei Wang

    (State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University, Shanghai 200092, China)

Abstract

Fatigue damage of yawed wind turbine components can be caused by repeated long-term unsteady asymmetric inflow loads across the rotor swept area, necessitating fatigue load analysis to ensure the in-operation safety of wind turbines. This study investigates the impact of geometric nonlinearity on the fatigue loads of wind turbine components. The geometrically exact beam theory (GEBT), implemented in BeamDyn of OpenFAST, is employed to model full geometric nonlinearity. For comparison, ElastoDyn in OpenFAST, which uses the generalized Euler–Bernoulli beam theory for straight isotropic beams, is also utilized. Aeroelastic simulations were conducted for the national renewable energy laboratory (NREL 5 MW) and international energy agency (IEA) 15 MW wind turbines. Fatigue loads, quantified by the damage equivalent load (DEL) based on Palmgren–Miner’s rule, were analyzed for critical components, including blade out-of-plane (OOP) moments, low-speed shaft (LSS) torque, LSS bending moment (LSSBM), and tower base bending moment (TBBM). Results indicate that geometric nonlinearity significantly influences fatigue damage in critical turbine components, with significant differences observed between BeamDyn and ElastoDyn simulations.

Suggested Citation

  • Dereje Haile Hirgeto & Guo-Wei Qian & Xuan-Yi Zhou & Wei Wang, 2025. "Fatigue Load Analysis of Yawed Wind Turbines Considering Geometric Nonlinearity of Blades," Energies, MDPI, vol. 18(19), pages 1-23, October.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:19:p:5290-:d:1765764
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/19/5290/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/18/19/5290/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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).
    2. Sun, Jili & Chen, Zheng & Yu, Hao & Gao, Shan & Wang, Bin & Ying, You & Sun, Yong & Qian, Peng & Zhang, Dahai & Si, Yulin, 2022. "Quantitative evaluation of yaw-misalignment and aerodynamic wake induced fatigue loads of offshore Wind turbines," Renewable Energy, Elsevier, vol. 199(C), pages 71-86.
    3. Wang, Lin & Liu, Xiongwei & Guo, Lianggang & Renevier, Nathalie & Stables, Matthew, 2014. "A mathematical model for calculating cross-sectional properties of modern wind turbine composite blades," Renewable Energy, Elsevier, vol. 64(C), pages 52-60.
    4. Wang, Baoxuan & Wang, Lizhong & Liang, Xu & Sheng, Fangyuan & Zhang, Jianwei & Hong, Yi & Wang, Lilin, 2024. "3D multiscale dynamic analysis of offshore wind turbine blade under fully coupled loads," Renewable Energy, Elsevier, vol. 223(C).
    Full references (including those not matched with items on IDEAS)

    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. 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).
    2. 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).
    3. Zhang, Teng & Xu, Xiaosen & Wang, Shuaishuai & Xing, Yihan & Dou, Peng & Ji, Renwei & Yang, Puyi, 2025. "Investigation of wake steering control effects on the dynamic responses of 15 MW semi-submersible floating wind farms," Renewable Energy, Elsevier, vol. 254(C).
    4. Wang, Yize & Liu, Zhenqing & Hu, Yilu & Bai, Guangpu, 2026. "A coherent power-load optimization algorithm for wind farm-level yaw control considering wake effects via deep neural network," Renewable Energy, Elsevier, vol. 257(C).
    5. Wang, Yize & Liu, Zhenqing, 2025. "Fatigue analysis of wind turbine and load reduction through wind-farm-level yaw control," Energy, Elsevier, vol. 326(C).
    6. Tiago R. Lucas Frutuoso & Rui Castro & Ricardo B. Santos Pereira & Alexandra Moutinho, 2025. "Advancements in Wind Farm Control: Modelling and Multi-Objective Optimization Through Yaw-Based Wake Steering," Energies, MDPI, vol. 18(9), pages 1-29, April.
    7. Sun, Jili & Yang, Jingqing & Jiang, Zezhong & Xu, JinFeng & Meng, Xiaofei & Feng, Xiaoguang & Si, Yulin & Zhang, Dahai, 2024. "Wake redirection control for offshore wind farm power and fatigue multi-objective optimisation based on a wind turbine load indicator," Energy, Elsevier, vol. 313(C).
    8. He, Ruiyang & Yang, Hongxing & Lu, Lin & Gao, Xiaoxia, 2024. "Site-specific wake steering strategy for combined power enhancement and fatigue mitigation within wind farms," Renewable Energy, Elsevier, vol. 225(C).
    9. 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.
    10. Saravia, Martín C. & Saravia, L. Joaquín & Cortínez, Víctor H., 2015. "A one dimensional discrete approach for the determination of the cross sectional properties of composite rotor blades," Renewable Energy, Elsevier, vol. 80(C), pages 713-723.
    11. Kumarasamy Palanimuthu & Ganesh Mayilsamy & Ameerkhan Abdul Basheer & Seong-Ryong Lee & Dongran Song & Young Hoon Joo, 2022. "A Review of Recent Aerodynamic Power Extraction Challenges in Coordinated Pitch, Yaw, and Torque Control of Large-Scale Wind Turbine Systems," Energies, MDPI, vol. 15(21), pages 1-27, November.
    12. Balakrishnan, Raj Kiran & Son, Eunkuk & Hur, Sung-ho, 2024. "Optimization of wind farm power output using wake redirection control," Renewable Energy, Elsevier, vol. 235(C).
    13. 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).
    14. Dong, Zhe & Li, Junyi & Zhang, Jiasen & Huang, Xiaojin & Dong, Yujie & Zhang, Zuoyi, 2024. "Nonlinear finite-set control of clean energy systems with nuclear power application," Energy, Elsevier, vol. 313(C).
    15. 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).
    16. Yang, Shanghui & Deng, Xiaowei & Li, Qinglan, 2025. "A joint optimization framework for power and fatigue life based on cooperative wake steering of wind farm," Energy, Elsevier, vol. 319(C).
    17. Shah, Owaisur Rahman & Tarfaoui, Mostapha, 2016. "The identification of structurally sensitive zones subject to failure in a wind turbine blade using nodal displacement based finite element sub-modeling," Renewable Energy, Elsevier, vol. 87(P1), pages 168-181.
    18. Dong, Fuxiang & Wang, Zhonghao & Mu, Chunjin & Liu, Jinfu & Yu, Daren & Li, Hong, 2025. "Wide angle range wind direction ultra-short-term interval prediction based on an improved loss function," Energy, Elsevier, vol. 334(C).
    19. Zhang, Xu & Zhang, Lijun & Wang, Kaifei & Cui, Xudong & Liu, Ziyi & Jing, Zhengjun & Liu, Shibo & Lu, Jiahui & Cai, Baoping, 2026. "Aerodynamic-structural similarity criteria for scaled-down models of ultra-long wind turbine blade," Renewable Energy, Elsevier, vol. 256(PD).
    20. Wang, Pengda & Xiao, Jinxin & Huang, Sheng & Wu, Qiuwei & Zhang, Menglin & Wu, Xuan & Shen, Feifan & Ma, Kuichao, 2025. "An accelerated asynchronous distributed control for DFIG wind turbines and collection system loss minimization in waked wind farm," Applied Energy, Elsevier, vol. 377(PD).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:gam:jeners:v:18:y:2025:i:19:p:5290-:d:1765764. 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 The email address of this maintainer does not seem to be valid anymore. Please ask MDPI Indexing Manager to update the entry or send us the correct address (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.