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Performance enhancement and load reduction of a 5 MW wind turbine blade

Author

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  • Vesel, Richard W.
  • McNamara, Jack J.

Abstract

A wind turbine rotor blade, based on the U.S. National Renewable Energy Laboratory (NREL) 5 MW reference turbine, is optimized for minimum cost of energy through simultaneous consideration of aerodynamics and bend-twist coupling. Eighty-three total design variables are considered, encompassing airfoil shapes, chord and twist distributions, and the degree of bend-twist coupling in the blade. A recently developed method requiring significantly less computation than finite element analysis is used for planning and predicting the bend-twist coupling behavior of the rotor. Airfoil performance is computed using XFOIL, while the wind turbine loads and performance are computed using the NREL FAST code. The objective function is annual cost of energy (COE), where reductions in flapwise bending loads and blade surface area are assumed to decrease rotor cost through reduced material requirements. The developed optimization process projects decreased blade loads while maintaining wind turbine performance.

Suggested Citation

  • Vesel, Richard W. & McNamara, Jack J., 2014. "Performance enhancement and load reduction of a 5 MW wind turbine blade," Renewable Energy, Elsevier, vol. 66(C), pages 391-401.
    • Handle: RePEc:eee:renene:v:66:y:2014:i:c:p:391-401
    DOI: 10.1016/j.renene.2013.12.019
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    References listed on IDEAS

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    1. Maheri, Alireza & Noroozi, Siamak & Vinney, John, 2007. "Application of combined analytical/FEA coupled aero-structure simulation in design of wind turbine adaptive blades," Renewable Energy, Elsevier, vol. 32(12), pages 2011-2018.
    2. de Goeij, W. C. & van Tooren, M. J. L. & Beukers, A., 1999. "Implementation of bending-torsion coupling in the design of a wind-turbine rotor-blade," Applied Energy, Elsevier, vol. 63(3), pages 191-207, July.
    3. Maheri, Alireza & Noroozi, Siamak & Vinney, John, 2007. "Combined analytical/FEA-based coupled aero structure simulation of a wind turbine with bend–twist adaptive blades," Renewable Energy, Elsevier, vol. 32(6), pages 916-930.
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    Cited by:

    1. Peng, Chao & Zou, Jianxiao & Li, Yan & Xu, Hongbing & Li, Liying, 2017. "A novel composite calculation model for power coefficient and flapping moment coefficient of wind turbine," Energy, Elsevier, vol. 126(C), pages 821-829.
    2. McKenna, R. & Ostman v.d. Leye, P. & Fichtner, W., 2016. "Key challenges and prospects for large wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 1212-1221.
    3. Scott, Samuel & Capuzzi, Marco & Langston, David & Bossanyi, Ervin & McCann, Graeme & Weaver, Paul M. & Pirrera, Alberto, 2017. "Effects of aeroelastic tailoring on performance characteristics of wind turbine systems," Renewable Energy, Elsevier, vol. 114(PB), pages 887-903.
    4. Zhu, Wei Jun & Shen, Wen Zhong & Sørensen, Jens Nørkær & Yang, Hua, 2017. "Verification of a novel innovative blade root design for wind turbines using a hybrid numerical method," Energy, Elsevier, vol. 141(C), pages 1661-1670.
    5. Jieyan Chen & Chengxi Li, 2020. "Design Optimization and Coupled Dynamics Analysis of an Offshore Wind Turbine with a Single Swivel Connected Tether," Energies, MDPI, vol. 13(14), pages 1-26, July.
    6. Nejra Beganovic & Jackson G. Njiri & Dirk Söffker, 2018. "Reduction of Structural Loads in Wind Turbines Based on an Adapted Control Strategy Concerning Online Fatigue Damage Evaluation Models," Energies, MDPI, vol. 11(12), pages 1-15, December.
    7. Zhenye Sun & Matias Sessarego & Jin Chen & Wen Zhong Shen, 2017. "Design of the OffWindChina 5 MW Wind Turbine Rotor," Energies, MDPI, vol. 10(6), pages 1-20, June.

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