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Uncertainty Quantification of the Effects of Blade Damage on the Actual Energy Production of Modern Wind Turbines

Author

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  • Francesco Papi

    (Department of Industrial Engineering, Università degli Studi di Firenze, 50139 Florence, Italy)

  • Lorenzo Cappugi

    (Department of Engineering, Lancaster University, Lancaster LA1 4YW, UK)

  • Simone Salvadori

    (Department of Energy, Politecnico di Torino, 10129 Torino, Italy)

  • Mauro Carnevale

    (Department of Mechanical Engineering, University of Bath, Bath BA2 7AY, UK)

  • Alessandro Bianchini

    (Department of Industrial Engineering, Università degli Studi di Firenze, 50139 Florence, Italy)

Abstract

Wind turbine blade deterioration issues have come to the attention of researchers and manufacturers due to the relevant impact they can have on the actual annual energy production (AEP). Research has shown how after prolonged exposure to hail, rain, insects or other abrasive particles, the outer surface of wind turbine blades deteriorates. This leads to increased surface roughness and material loss. The trailing edge (TE) of the blade is also often damaged during assembly and transportation according to industry veterans. This study aims at investigating the loss of AEP and efficiency of modern multi-MW wind turbines due to such issues using uncertainty quantification. Such an approach is justified by the stochastic and widely different environmental conditions in which wind turbines are installed. These cause uncertainties regarding the blade’s conditions. To this end, the test case selected for the study is the DTU 10 MW reference wind turbine (RWT), a modern reference turbine with a rated power of 10 MW. Blade damage is modelled through shape modification of the turbine’s airfoils. This is done with a purposely developed numerical tool. Lift and drag coefficients for the damaged airfoils are calculated using computational fluid dynamics. The resulting lift and drag coefficients are used in an aero-servo-elastic model of the wind turbine using NREL’s code OpenFAST. An arbitrary polynomial chaos expansion method is used to estimate the probability distributions of AEP and power output of the model when blade damage is present. Average AEP losses of around 1% are predicted mainly due to leading-edge blade damage. Results show that the proposed method is able to account for the uncertainties and to give more meaningful information with respect to the simulation of a single test case.

Suggested Citation

  • Francesco Papi & Lorenzo Cappugi & Simone Salvadori & Mauro Carnevale & Alessandro Bianchini, 2020. "Uncertainty Quantification of the Effects of Blade Damage on the Actual Energy Production of Modern Wind Turbines," Energies, MDPI, vol. 13(15), pages 1-18, July.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:15:p:3785-:d:388775
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    References listed on IDEAS

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    1. Herring, Robbie & Dyer, Kirsten & Martin, Ffion & Ward, Carwyn, 2019. "The increasing importance of leading edge erosion and a review of existing protection solutions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    2. Matthias Schramm & Hamid Rahimi & Bernhard Stoevesandt & Kim Tangager, 2017. "The Influence of Eroded Blades on Wind Turbine Performance Using Numerical Simulations," Energies, MDPI, vol. 10(9), pages 1-15, September.
    3. Han, Woobeom & Kim, Jonghwa & Kim, Bumsuk, 2018. "Effects of contamination and erosion at the leading edge of blade tip airfoils on the annual energy production of wind turbines," Renewable Energy, Elsevier, vol. 115(C), pages 817-823.
    4. Oladyshkin, S. & Nowak, W., 2012. "Data-driven uncertainty quantification using the arbitrary polynomial chaos expansion," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 179-190.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

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    2. Giovanni Ferrara & Alessandro Bianchini, 2021. "Special Issue “Numerical Simulation of Wind Turbines”," Energies, MDPI, vol. 14(6), pages 1-2, March.
    3. He, Rui & Tian, Zhigang & Wang, Yifei & Zuo, Mingjian & Guo, Ziwei, 2023. "Condition-based maintenance optimization for multi-component systems considering prognostic information and degraded working efficiency," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    4. Thapa, Mishal & Missoum, Samy, 2022. "Uncertainty quantification and global sensitivity analysis of composite wind turbine blades," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    5. Giulio Vita & Syeda Anam Hashmi & Simone Salvadori & Hassan Hemida & Charalampos Baniotopoulos, 2020. "Role of Inflow Turbulence and Surrounding Buildings on Large Eddy Simulations of Urban Wind Energy," Energies, MDPI, vol. 13(19), pages 1-22, October.
    6. Jeanie A. Aird & Rebecca J. Barthelmie & Sara C. Pryor, 2023. "Automated Quantification of Wind Turbine Blade Leading Edge Erosion from Field Images," Energies, MDPI, vol. 16(6), pages 1-23, March.

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