IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i16p4988-d614269.html
   My bibliography  Save this article

The Effect of a Flexible Blade for Load Alleviation in Wind Turbines

Author

Listed:
  • Azael Duran Castillo

    (Faculty of Engineering, Universidad Autonoma de Queretaro, Cerro de las Campanas S/N, Queretaro 76010, Mexico)

  • Juan C. Jauregui-Correa

    (Faculty of Engineering, Universidad Autonoma de Queretaro, Cerro de las Campanas S/N, Queretaro 76010, Mexico)

  • Francisco Herbert

    (Mechanical Engineering Department, Texas Sustainable Energy Research Institute, University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249, USA)

  • Krystel K. Castillo-Villar

    (Mechanical Engineering Department, Texas Sustainable Energy Research Institute, University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249, USA)

  • Jesus Alejandro Franco

    (Escuela Nacional de Estudios Superiores Unidad Juriquilla, UNAM, Queretaro 76230, Mexico)

  • Quetzalcoatl Hernandez-Escobedo

    (Escuela Nacional de Estudios Superiores Unidad Juriquilla, UNAM, Queretaro 76230, Mexico)

  • Alberto-Jesus Perea-Moreno

    (Departamento de Física Aplicada, Radiología y Medicina Física, Universidad de Córdoba, Campus de Rabanales, 14071 Córdoba, Spain)

  • Alfredo Alcayde

    (Department of Engineering, University of Almería, La Cañada de San Urbano, 04120 Almería, Spain)

Abstract

This article presents the analysis of the performance of a flexible wind turbine blade. The simulation analysis is based on a 3 m span blade prototype. The blade has a flexible surface and a cam mechanism that modifies the aerodynamic profile and adapts the surface to different configurations. The blade surface was built with a flexible fiberglass composite, and the internal mechanism consists of a flexible structure actuated with an eccentric cam. The cam mechanism deforms five sections of the blade, and the airfoil geometry for each section was measured from zero cam displacement to full cam displacement. The measured data were interpolated to obtain the aerodynamic profiles of the five sections to model the flexible blade in the simulation process. The simulation analysis consisted of determining the different aerodynamic coefficients for different deformed surfaces and a range of wind speeds. The aerodynamic coefficients were calculated with the BEM method (QBlade ® ); as a result, the data performance of the flexible blade was compared for the different deformation configurations. Finally, a decrease of up to approximately 6% in the mean bending moment suggests that the flexible turbine rotor presented in this article can be used to reduce extreme and fatigue loads on wind turbines.

Suggested Citation

  • Azael Duran Castillo & Juan C. Jauregui-Correa & Francisco Herbert & Krystel K. Castillo-Villar & Jesus Alejandro Franco & Quetzalcoatl Hernandez-Escobedo & Alberto-Jesus Perea-Moreno & Alfredo Alcayd, 2021. "The Effect of a Flexible Blade for Load Alleviation in Wind Turbines," Energies, MDPI, vol. 14(16), pages 1-15, August.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:16:p:4988-:d:614269
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/16/4988/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/16/4988/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Momeni, Farhang & Sabzpoushan, Seyedali & Valizadeh, Reza & Morad, Mohammad Reza & Liu, Xun & Ni, Jun, 2019. "Plant leaf-mimetic smart wind turbine blades by 4D printing," Renewable Energy, Elsevier, vol. 130(C), pages 329-351.
    2. Chen, Bei & Hua, Xugang & Zhang, Zili & Nielsen, Søren R.K. & Chen, Zhengqing, 2021. "Active flutter control of the wind turbines using double-pitched blades," Renewable Energy, Elsevier, vol. 163(C), pages 2081-2097.
    3. Cognet, V. & Courrech du Pont, S. & Thiria, B., 2020. "Material optimization of flexible blades for wind turbines," Renewable Energy, Elsevier, vol. 160(C), pages 1373-1384.
    4. Boulamatsis, Achilles M. & Barlas, Thanasis K. & Stapountzis, Herricos, 2019. "Active control of wind turbines through varying blade tip sweep," Renewable Energy, Elsevier, vol. 131(C), pages 25-36.
    5. Zhuang, Chen & Yang, Gang & Zhu, Yawei & Hu, Dean, 2020. "Effect of morphed trailing-edge flap on aerodynamic load control for a wind turbine blade section," Renewable Energy, Elsevier, vol. 148(C), pages 964-974.
    6. MacPhee, David W. & Beyene, Asfaw, 2019. "Performance analysis of a small wind turbine equipped with flexible blades," Renewable Energy, Elsevier, vol. 132(C), pages 497-508.
    7. Chen, Hao & Qin, Ning, 2017. "Trailing-edge flow control for wind turbine performance and load control," Renewable Energy, Elsevier, vol. 105(C), pages 419-435.
    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. Abdulbasit Mohammed & Belete Sirahbizu & Hirpa G. Lemu, 2022. "Optimal Rotary Wind Turbine Blade Modeling with Bond Graph Approach for Specific Local Sites," Energies, MDPI, vol. 15(18), pages 1-17, September.
    2. Alfredo Alcayde & Quetzalcoatl Hernandez-Escobedo & David Muñoz-Rodríguez & Alberto-Jesus Perea-Moreno, 2022. "Worldwide Research Trends on Optimizing Wind Turbine Efficiency," Energies, MDPI, vol. 15(18), pages 1-7, September.
    3. Banteng Liu & Yangqing Xie & Ke Wang & Lizhe Yu & Ying Zhou & Xiaowen Lv, 2023. "Short-Term Multi-Step Wind Direction Prediction Based on OVMD Quadratic Decomposition and LSTM," Sustainability, MDPI, vol. 15(15), pages 1-18, July.

    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. Koca, Kemal & Genç, Mustafa Serdar & Ertürk, Sevde, 2022. "Impact of local flexible membrane on power efficiency stability at wind turbine blade," Renewable Energy, Elsevier, vol. 197(C), pages 1163-1173.
    2. Tingrui Liu & Ailing Gong & Changle Song & Yuehua Wang, 2020. "Sliding Mode Control of Active Trailing-Edge Flap Based on Adaptive Reaching Law and Minimum Parameter Learning of Neural Networks," Energies, MDPI, vol. 13(5), pages 1-21, February.
    3. Guoqiang, Li & Weiguo, Zhang & Yubiao, Jiang & Pengyu, Yang, 2019. "Experimental investigation of dynamic stall flow control for wind turbine airfoils using a plasma actuator," Energy, Elsevier, vol. 185(C), pages 90-101.
    4. Ebrahimi, Abbas & Movahhedi, Mohammadreza, 2018. "Wind turbine power improvement utilizing passive flow control with microtab," Energy, Elsevier, vol. 150(C), pages 575-582.
    5. Md Zishan Akhter & Farag Khalifa Omar, 2021. "Review of Flow-Control Devices for Wind-Turbine Performance Enhancement," Energies, MDPI, vol. 14(5), pages 1-35, February.
    6. José Luis Torres-Madroñero & Joham Alvarez-Montoya & Daniel Restrepo-Montoya & Jorge Mario Tamayo-Avendaño & César Nieto-Londoño & Julián Sierra-Pérez, 2020. "Technological and Operational Aspects That Limit Small Wind Turbines Performance," Energies, MDPI, vol. 13(22), pages 1-39, November.
    7. Sun, Jinjing & Sun, Xiaojing & Huang, Diangui, 2020. "Aerodynamics of vertical-axis wind turbine with boundary layer suction – Effects of suction momentum," Energy, Elsevier, vol. 209(C).
    8. Gambuzza, Stefano & Pisetta, Gabriele & Davey, Thomas & Steynor, Jeffrey & Viola, Ignazio Maria, 2023. "Model-scale experiments of passive pitch control for tidal turbines," Renewable Energy, Elsevier, vol. 205(C), pages 10-29.
    9. Song, Jeonghwan & Kim, Taewan & You, Donghyun, 2023. "Particle swarm optimization of a wind farm layout with active control of turbine yaws," Renewable Energy, Elsevier, vol. 206(C), pages 738-747.
    10. Muhammad Shahzad Nazir & Fahad Alturise & Sami Alshmrany & Hafiz. M. J Nazir & Muhammad Bilal & Ahmad N. Abdalla & P. Sanjeevikumar & Ziad M. Ali, 2020. "Wind Generation Forecasting Methods and Proliferation of Artificial Neural Network: A Review of Five Years Research Trend," Sustainability, MDPI, vol. 12(9), pages 1-27, May.
    11. Hércules Araújo Oliveira & José Gomes de Matos & Luiz Antonio de Souza Ribeiro & Osvaldo Ronald Saavedra & Jerson Rogério Pinheiro Vaz, 2023. "Assessment of Correction Methods Applied to BEMT for Predicting Performance of Horizontal-Axis Wind Turbines," Sustainability, MDPI, vol. 15(8), pages 1-26, April.
    12. Shahzad Ali, Qazi & Kim, Man-Hoe, 2022. "Quantifying impacts of shell augmentation on power output of airborne wind energy system at elevated heights," Energy, Elsevier, vol. 239(PA).
    13. Liu, Zhen & Qu, Hengliang, 2022. "Numerical study on a coupled-pitching flexible hydrofoil under the semi-passive mode," Renewable Energy, Elsevier, vol. 189(C), pages 339-358.
    14. Zhanpu Xue & Hao Zhang & Yunguang Ji, 2023. "Dynamic Response of a Flexible Multi-Body in Large Wind Turbines: A Review," Sustainability, MDPI, vol. 15(8), pages 1-25, April.
    15. Gorle, J.M.R. & Chatellier, L. & Pons, F. & Ba, M., 2019. "Modulated circulation control around the blades of a vertical axis hydrokinetic turbine for flow control and improved performance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 363-377.
    16. Wang, Longyan & Xu, Jian & Wang, Zilu & Zhang, Bowen & Luo, Zhaohui & Yuan, Jianping & Tan, Andy C.C., 2023. "A novel cost-efficient deep learning framework for static fluid–structure interaction analysis of hydrofoil in tidal turbine morphing blade," Renewable Energy, Elsevier, vol. 208(C), pages 367-384.
    17. Azlan, F. & Tan, M.K. & Tan, B.T. & Ismadi, M.-Z., 2023. "Passive flow-field control using dimples for performance enhancement of horizontal axis wind turbine," Energy, Elsevier, vol. 271(C).
    18. Xue, Zhanpu & Wang, Wei & Fang, Liqing & Zhou, Jingbo, 2020. "Numerical simulation on structural dynamics of 5 MW wind turbine," Renewable Energy, Elsevier, vol. 162(C), pages 222-233.
    19. Abdulbasit Mohammed & Belete Sirahbizu & Hirpa G. Lemu, 2022. "Optimal Rotary Wind Turbine Blade Modeling with Bond Graph Approach for Specific Local Sites," Energies, MDPI, vol. 15(18), pages 1-17, September.
    20. Yu-Ting Wu & Chang-Yu Lin & Che-Ming Hsu, 2020. "An Experimental Investigation of Wake Characteristics and Power Generation Efficiency of a Small Wind Turbine under Different Tip Speed Ratios," Energies, MDPI, vol. 13(8), pages 1-19, April.

    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:14:y:2021:i:16:p:4988-:d:614269. 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 (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.