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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
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    References listed on IDEAS

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    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. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
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    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.

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