IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v83y2015icp859-870.html
   My bibliography  Save this article

A dual de-icing system for wind turbine blades combining high-power ultrasonic guided waves and low-frequency forced vibrations

Author

Listed:
  • Habibi, Hossein
  • Cheng, Liang
  • Zheng, Haitao
  • Kappatos, Vassilios
  • Selcuk, Cem
  • Gan, Tat-Hean

Abstract

Wind turbines mounted on cold climate sites are subject to icing which could significantly influence the performance of the turbine blades for harvesting wind energy. In this study, an innovative dual de-icing system under development is described. This either prevents ice accumulation (anti-icing) or removes any ice layer present on the surface of the blade material (de-icing). A modelling study on ultrasonic guided waves propagating in composite blades was used to determine the optimal frequency and location of the transducers for ensuring wave propagation, causing the required level of energy concentration and resulting shear stress across the leading edge of the turbine's blade. In parallel, the effects of low frequency vibrations have been investigated through modal and harmonic analyses. This allowed specification and optimisation of the positioning of shaker(s), together with the magnitude and direction of harmonic forces required to induce sufficient acceleration to the blade surface for ice removal. An appropriate survey was also carried out to evaluate the potential for fatigue failure of the blade due to harmonic forces induced by shakers. The proposed technique configures and presents an active solution for the icing problem, allowing safe and reliable operation of wind turbines in adverse weather conditions.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:renene:v:83:y:2015:i:c:p:859-870
    DOI: 10.1016/j.renene.2015.05.025
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148115004048
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2015.05.025?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. 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.
    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. Dong, Xinghui & Gao, Di & Li, Jia & Jincao, Zhang & Zheng, Kai, 2020. "Blades icing identification model of wind turbines based on SCADA data," Renewable Energy, Elsevier, vol. 162(C), pages 575-586.
    2. Wang, Yibing & Xu, Yuanming & Lei, Yuyong, 2018. "An effect assessment and prediction method of ultrasonic de-icing for composite wind turbine blades," Renewable Energy, Elsevier, vol. 118(C), pages 1015-1023.
    3. 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.
    4. Chen, Bin & Yu, Songhao & Yu, Yang & Zhou, Yilin, 2020. "Acoustical damage detection of wind turbine blade using the improved incremental support vector data description," Renewable Energy, Elsevier, vol. 156(C), pages 548-557.
    5. Sudhakar Gantasala & Jean-Claude Luneno & Jan-Olov Aidanpää, 2017. "Investigating How an Artificial Neural Network Model Can Be Used to Detect Added Mass on a Non-Rotating Beam Using Its Natural Frequencies: A Possible Application for Wind Turbine Blade Ice Detection," Energies, MDPI, vol. 10(2), pages 1-21, February.
    6. Madi, Ezieddin & Pope, Kevin & Huang, Weimin & Iqbal, Tariq, 2019. "A review of integrating ice detection and mitigation for wind turbine blades," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 269-281.
    7. Ma, Liqun & Zhang, Zichen & Gao, Linyue & Liu, Yang & Hu, Hui, 2020. "An exploratory study on using Slippery-Liquid-Infused-Porous-Surface (SLIPS) for wind turbine icing mitigation," Renewable Energy, Elsevier, vol. 162(C), pages 2344-2360.
    8. Yan Li & He Shen & Wenfeng Guo, 2021. "Simulation and Experimental Study on the Ultrasonic Micro-Vibration De-Icing Method for Wind Turbine Blades," Energies, MDPI, vol. 14(24), pages 1-15, December.
    9. Jiménez, Alfredo Arcos & García Márquez, Fausto Pedro & Moraleda, Victoria Borja & Gómez Muñoz, Carlos Quiterio, 2019. "Linear and nonlinear features and machine learning for wind turbine blade ice detection and diagnosis," Renewable Energy, Elsevier, vol. 132(C), pages 1034-1048.
    10. Zeng, Jing & Song, Bingliang, 2017. "Research on experiment and numerical simulation of ultrasonic de-icing for wind turbine blades," Renewable Energy, Elsevier, vol. 113(C), pages 706-712.
    11. Wang, Yibing & Xu, Yuanming & Su, Fei, 2020. "Damage accumulation model of ice detach behavior in ultrasonic de-icing technology," Renewable Energy, Elsevier, vol. 153(C), pages 1396-1405.
    12. Liu, Wenyi, 2016. "Design and kinetic analysis of wind turbine blade-hub-tower coupled system," Renewable Energy, Elsevier, vol. 94(C), pages 547-557.
    13. Wang, Yibing & Xu, Yuanming & Huang, Qi, 2017. "Progress on ultrasonic guided waves de-icing techniques in improving aviation energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 638-645.
    14. Sun, Shilin & Wang, Tianyang & Chu, Fulei, 2022. "In-situ condition monitoring of wind turbine blades: A critical and systematic review of techniques, challenges, and futures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    15. Jiawei Jiang & Yizhou Shen & Yangjiangshan Xu & Zhen Wang & Jie Tao & Senyun Liu & Weilan Liu & Haifeng Chen, 2024. "An energy-free strategy to elevate anti-icing performance of superhydrophobic materials through interfacial airflow manipulation," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    16. Kaewniam, Panida & Cao, Maosen & Alkayem, Nizar Faisal & Li, Dayang & Manoach, Emil, 2022. "Recent advances in damage detection of wind turbine blades: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).

    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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.

    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:renene:v:83:y:2015:i:c:p:859-870. 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/renewable-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.