IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v30y2005i11p2101-2114.html
   My bibliography  Save this article

Structural investigation of composite wind turbine blade considering various load cases and fatigue life

Author

Listed:
  • Kong, C.
  • Bang, J.
  • Sugiyama, Y.

Abstract

This study proposes a structural design for developing a medium scale composite wind turbine blade made of E-glass/epoxy for a 750kW class horizontal axis wind turbine system. The design loads were determined from various load cases specified at the IEC61400-1 international specification and GL regulations for the wind energy conversion system. A specific composite structure configuration, which can effectively endure various loads such as aerodynamic loads and loads due to accumulation of ice, hygro-thermal and mechanical loads, was proposed. To evaluate the proposed composite wind turbine blade, structural analysis was performed by using the finite element method. Parametric studies were carried out to determine an acceptable blade structural design, and the most dominant design parameters were confirmed. In this study, the proposed blade structure was confirmed to be safe and stable under various load conditions, including the extreme load conditions. Moreover, the blade adapted a new blade root joint with insert bolts, and its safety was verified at design loads including fatigue loads. The fatigue life of a blade that has to endure for more than 20 years was estimated by using the well-known S–N linear damage theory, the service load spectrum, and the Spera's empirical equations. With the results obtained from all the structural design and analysis, prototype composite blades were manufactured. A specific construction process including the lay-up molding method was applied to manufacturing blades. Full-scale static structural test was performed with the simulated aerodynamic loads. From the experimental results, it was found that the designed blade had structural integrity. In addition, the measured results of deflections, strains, mass, and radial center of gravity agreed well with the analytical results. The prototype blade was successfully certified by an international certification institute, GL (Germanisher Lloyd) in Germany.

Suggested Citation

  • Kong, C. & Bang, J. & Sugiyama, Y., 2005. "Structural investigation of composite wind turbine blade considering various load cases and fatigue life," Energy, Elsevier, vol. 30(11), pages 2101-2114.
  • Handle: RePEc:eee:energy:v:30:y:2005:i:11:p:2101-2114
    DOI: 10.1016/j.energy.2004.08.016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054420400369X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2004.08.016?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Inomata, N. & Tsuchiya, K. & Yamada, S., 1999. "Measurement of stress on blade of NEDO's 500 kW prototype wind turbine," Renewable Energy, Elsevier, vol. 16(1), pages 912-915.
    2. Ackermann, Thomas & Söder, Lennart, 2000. "Wind energy technology and current status: a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 4(4), pages 315-374, December.
    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. Philipp R Thies & Lars Johanning & Kwaku Ampea Karikari-Boateng & Chong Ng & Paul McKeever, 2015. "Component reliability test approaches for marine renewable energy," Journal of Risk and Reliability, , vol. 229(5), pages 403-416, October.
    2. Wei Li & Shinai Xu & Baiyun Qian & Xiaoxia Gao & Xiaoxun Zhu & Zeqi Shi & Wei Liu & Qiaoliang Hu, 2022. "Large-Scale Wind Turbine’s Load Characteristics Excited by the Wind and Grid in Complex Terrain: A Review," Sustainability, MDPI, vol. 14(24), pages 1-29, December.
    3. Ozbek, Muammer & Rixen, Daniel J. & Erne, Oliver & Sanow, Gunter, 2010. "Feasibility of monitoring large wind turbines using photogrammetry," Energy, Elsevier, vol. 35(12), pages 4802-4811.
    4. Beganovic, Nejra & Söffker, Dirk, 2016. "Structural health management utilization for lifetime prognosis and advanced control strategy deployment of wind turbines: An overview and outlook concerning actual methods, tools, and obtained result," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 68-83.
    5. Radičević, Branko M. & Savić, Milan S. & Madsen, Søren Find & Badea, Ion, 2012. "Impact of wind turbine blade rotation on the lightning strike incidence – A theoretical and experimental study using a reduced-size model," Energy, Elsevier, vol. 45(1), pages 644-654.
    6. Lu, Liang & Wu, Haijun & Wu, Jianzhong, 2021. "A case study for the optimization of moment-matching in wind turbine blade fatigue tests with a resonant type exciting approach," Renewable Energy, Elsevier, vol. 174(C), pages 769-785.
    7. Senthil Kumar Madasamy & Vijayanandh Raja & Hussein A Z AL-bonsrulah & Mohammed Al-Bahrani, 2022. "Design, development and multi-disciplinary investigations of aerodynamic, structural, energy and exergy factors on 1 kW horizontal-axis wind turbine [Composite materials for wind power turbine blad," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 17, pages 1292-1318.
    8. Peter J. Schubel & Richard J. Crossley, 2012. "Wind Turbine Blade Design," Energies, MDPI, vol. 5(9), pages 1-25, September.
    9. Liao, C.C. & Zhao, X.L. & Xu, J.Z., 2012. "Blade layers optimization of wind turbines using FAST and improved PSO Algorithm," Renewable Energy, Elsevier, vol. 42(C), pages 227-233.
    10. Jinghua Lin & You-lin Xu & Yong Xia, 2019. "Structural Analysis of Large-Scale Vertical Axis Wind Turbines Part II: Fatigue and Ultimate Strength Analyses," Energies, MDPI, vol. 12(13), pages 1-18, July.
    11. Dimitris Al. Katsaprakakis & Nikos Papadakis & Ioannis Ntintakis, 2021. "A Comprehensive Analysis of Wind Turbine Blade Damage," Energies, MDPI, vol. 14(18), pages 1-31, September.
    12. Tjiu, Willy & Marnoto, Tjukup & Mat, Sohif & Ruslan, Mohd Hafidz & Sopian, Kamaruzzaman, 2015. "Darrieus vertical axis wind turbine for power generation II: Challenges in HAWT and the opportunity of multi-megawatt Darrieus VAWT development," Renewable Energy, Elsevier, vol. 75(C), pages 560-571.
    13. Habibi, Hossein & Cheng, Liang & Zheng, Haitao & Kappatos, Vassilios & Selcuk, Cem & Gan, Tat-Hean, 2015. "A dual de-icing system for wind turbine blades combining high-power ultrasonic guided waves and low-frequency forced vibrations," Renewable Energy, Elsevier, vol. 83(C), pages 859-870.
    14. Liao, Ding & Zhu, Shun-Peng & Correia, José A.F.O. & De Jesus, Abílio M.P. & Veljkovic, Milan & Berto, Filippo, 2022. "Fatigue reliability of wind turbines: historical perspectives, recent developments and future prospects," Renewable Energy, Elsevier, vol. 200(C), pages 724-742.
    15. Xin Cai & Jie Zhu & Pan Pan & Rongrong Gu, 2012. "Structural Optimization Design of Horizontal-Axis Wind Turbine Blades Using a Particle Swarm Optimization Algorithm and Finite Element Method," Energies, MDPI, vol. 5(11), pages 1-14, November.
    16. Yang, Jinshui & Peng, Chaoyi & Xiao, Jiayu & Zeng, Jingcheng & Yuan, Yun, 2012. "Application of videometric technique to deformation measurement for large-scale composite wind turbine blade," Applied Energy, Elsevier, vol. 98(C), pages 292-300.
    17. Marín, J.C. & Barroso, A. & París, F. & Cañas, J., 2008. "Study of damage and repair of blades of a 300kW wind turbine," Energy, Elsevier, vol. 33(7), pages 1068-1083.
    18. Jie Zhu & Xin Cai & Pan Pan & Rongrong Gu, 2014. "Multi-Objective Structural Optimization Design of Horizontal-Axis Wind Turbine Blades Using the Non-Dominated Sorting Genetic Algorithm II and Finite Element Method," Energies, MDPI, vol. 7(2), pages 1-15, February.
    19. Dai, Juchuan & Li, Mimi & Chen, Huanguo & He, Tao & Zhang, Fan, 2022. "Progress and challenges on blade load research of large-scale wind turbines," Renewable Energy, Elsevier, vol. 196(C), pages 482-496.
    20. Chehouri, Adam & Younes, Rafic & Ilinca, Adrian & Perron, Jean, 2015. "Review of performance optimization techniques applied to wind turbines," Applied Energy, Elsevier, vol. 142(C), pages 361-388.
    21. Zhiyu Jiang & Weifei Hu & Wenbin Dong & Zhen Gao & Zhengru Ren, 2017. "Structural Reliability Analysis of Wind Turbines: A Review," Energies, MDPI, vol. 10(12), pages 1-25, December.
    22. Xiao Chen & Wei Zhao & Xiao Lu Zhao & Jian Zhong Xu, 2014. "Failure Test and Finite Element Simulation of a Large Wind Turbine Composite Blade under Static Loading," Energies, MDPI, vol. 7(4), pages 1-24, April.
    23. Jiang, Wenchun & Fan, Qinshan & Gong, Jianming, 2010. "Optimization of welding joint between tower and bottom flange based on residual stress considerations in a wind turbine," Energy, Elsevier, vol. 35(1), pages 461-467.

    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. Mehrjoo, Mehrdad & Jafari Jozani, Mohammad & Pawlak, Miroslaw, 2021. "Toward hybrid approaches for wind turbine power curve modeling with balanced loss functions and local weighting schemes," Energy, Elsevier, vol. 218(C).
    2. Wang, Jianzhou & Wang, Shuai & Li, Zhiwu, 2021. "Wind speed deterministic forecasting and probabilistic interval forecasting approach based on deep learning, modified tunicate swarm algorithm, and quantile regression," Renewable Energy, Elsevier, vol. 179(C), pages 1246-1261.
    3. Jha, Sunil Kr. & Bilalovic, Jasmin & Jha, Anju & Patel, Nilesh & Zhang, Han, 2017. "Renewable energy: Present research and future scope of Artificial Intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 297-317.
    4. Zeynep Ökten & Þenol Adýgüzel, 2006. "Transforming the Problems into Opportunities in Energy Sector," Papers of the Annual IUE-SUNY Cortland Conference in Economics, in: Oguz Esen & Ayla Ogus (ed.), Proceedings of the Conference on Human and Economic Resources, pages 126-139, Izmir University of Economics.
    5. Chen, Xia & Fu, Qiang & Chang, Chun-Ping, 2021. "What are the shocks of climate change on clean energy investment: A diversified exploration," Energy Economics, Elsevier, vol. 95(C).
    6. Gebreslassie, Mulualem G., 2020. "Public perception and policy implications towards the development of new wind farms in Ethiopia," Energy Policy, Elsevier, vol. 139(C).
    7. Milanese, Marco & Tornese, Ljuba & Colangelo, Gianpiero & Laforgia, Domenico & de Risi, Arturo, 2017. "Numerical method for wind energy analysis applied to Apulia Region, Italy," Energy, Elsevier, vol. 128(C), pages 1-10.
    8. Olatayo, Kunle Ibukun & Wichers, J. Harry & Stoker, Piet W., 2018. "Energy and economic performance of small wind energy systems under different climatic conditions of South Africa," Renewable and Sustainable Energy Reviews, Elsevier, vol. 98(C), pages 376-392.
    9. Meratizaman, Mousa & Nateqi, Mojtaba, 2021. "Feasibility study of new generation of wind turbine (INVELOX), is it competitive with the Conventional Horizontal Axis Wind Turbine?," Energy, Elsevier, vol. 217(C).
    10. Yoonhwan Oh & Jungsub Yoon & Jeong-Dong Lee, 2016. "Evolutionary Patterns of Renewable Energy Technology Development in East Asia (1990–2010)," Sustainability, MDPI, vol. 8(8), pages 1-24, July.
    11. Jiang, Wenchun & Fan, Qinshan & Gong, Jianming, 2010. "Optimization of welding joint between tower and bottom flange based on residual stress considerations in a wind turbine," Energy, Elsevier, vol. 35(1), pages 461-467.
    12. Xu, Jiuping & Li, Li & Zheng, Bobo, 2016. "Wind energy generation technological paradigm diffusion," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 436-449.
    13. Mohd Zin, Abdullah Asuhaimi B. & Pesaran H.A., Mahmoud & Khairuddin, Azhar B. & Jahanshaloo, Leila & Shariati, Omid, 2013. "An overview on doubly fed induction generators′ controls and contributions to wind based electricity generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 692-708.
    14. Sürgevil, Tolga & Akpınar, Eyüp, 2005. "Modelling of a 5-kW wind energy conversion system with induction generator and comparison with experimental results," Renewable Energy, Elsevier, vol. 30(6), pages 913-929.
    15. Hossain, Md Maruf & Ali, Mohd. Hasan, 2015. "Future research directions for the wind turbine generator system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 481-489.
    16. Himri, Y. & Rehman, S. & Draoui, B. & Himri, S., 2008. "Wind power potential assessment for three locations in Algeria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(9), pages 2495-2504, December.
    17. Bilgili, Mehmet & Yasar, Abdulkadir & Simsek, Erdogan, 2011. "Offshore wind power development in Europe and its comparison with onshore counterpart," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(2), pages 905-915, February.
    18. Dragomir, George & Șerban, Alexandru & Năstase, Gabriel & Brezeanu, Alin Ionuț, 2016. "Wind energy in Romania: A review from 2009 to 2016," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 129-143.
    19. Jiang, Ping & Wang, Biao & Li, Hongmin & Lu, Haiyan, 2019. "Modeling for chaotic time series based on linear and nonlinear framework: Application to wind speed forecasting," Energy, Elsevier, vol. 173(C), pages 468-482.
    20. Wang, Shuai & Wang, Jianzhou & Lu, Haiyan & Zhao, Weigang, 2021. "A novel combined model for wind speed prediction – Combination of linear model, shallow neural networks, and deep learning approaches," Energy, Elsevier, vol. 234(C).

    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:30:y:2005:i:11:p:2101-2114. 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.