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Effects of contamination and erosion at the leading edge of blade tip airfoils on the annual energy production of wind turbines

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  • Han, Woobeom
  • Kim, Jonghwa
  • Kim, Bumsuk

Abstract

Contamination and erosion at the leading edge of blade tips adversely affect the annual energy production (AEP) of wind turbines. Obtaining pertinent quantitative data would help in the efficient planning of operations and maintenance of these turbines. In this study, to quantitatively analyze the effects of contamination and erosion on the aerodynamic performance of a blade tip airfoil (NACA 64-618) and in turn on the AEP loss of wind turbines, transient computational fluid dynamics simulations and AEP calculations were performed for a 5-MW National Renewable Energy Laboratory wind turbine. The simulations indicated that depending on the severity of the conditions, contamination and erosion conditions reduced and increased the lift and drag coefficients, respectively, of the blade by up to 53% and 314%. Contamination and erosion conditions reduced AEP by 2%–3.7%.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:renene:v:115:y:2018:i:c:p:817-823
    DOI: 10.1016/j.renene.2017.09.002
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    References listed on IDEAS

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    Cited by:

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    9. Papi, Francesco & Balduzzi, Francesco & Ferrara, Giovanni & Bianchini, Alessandro, 2021. "Uncertainty quantification on the effects of rain-induced erosion on annual energy production and performance of a Multi-MW wind turbine," Renewable Energy, Elsevier, vol. 165(P1), pages 701-715.
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    14. Pugh, K. & Nash, J.W. & Reaburn, G. & Stack, M.M., 2021. "On analytical tools for assessing the raindrop erosion of wind turbine blades," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    15. Charlotte Bay Hasager & Flemming Vejen & Witold Robert Skrzypiński & Anna-Maria Tilg, 2021. "Rain Erosion Load and Its Effect on Leading-Edge Lifetime and Potential of Erosion-Safe Mode at Wind Turbines in the North Sea and Baltic Sea," Energies, MDPI, vol. 14(7), pages 1-24, April.
    16. Sergio Campobasso, M. & Castorrini, Alessio & Ortolani, Andrea & Minisci, Edmondo, 2023. "Probabilistic analysis of wind turbine performance degradation due to blade erosion accounting for uncertainty of damage geometry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 178(C).
    17. Koodly Ravishankara, Akshay & Özdemir, Huseyin & van der Weide, Edwin, 2021. "Analysis of leading edge erosion effects on turbulent flow over airfoils," Renewable Energy, Elsevier, vol. 172(C), pages 765-779.
    18. Yang, Muchen & Xiao, Zhixiang, 2019. "Distributed roughness induced transition on wind-turbine airfoils simulated by four-equation k-ω-γ-Ar transition model," Renewable Energy, Elsevier, vol. 135(C), pages 1166-1177.
    19. Mikkel Schou Nielsen & Ivan Nikolov & Emil Krog Kruse & Jørgen Garnæs & Claus Brøndgaard Madsen, 2020. "High-Resolution Structure-from-Motion for Quantitative Measurement of Leading-Edge Roughness," Energies, MDPI, vol. 13(15), pages 1-17, July.
    20. Dollinger, Christoph & Balaresque, Nicholas & Gaudern, Nicholas & Gleichauf, Daniel & Sorg, Michael & Fischer, Andreas, 2019. "IR thermographic flow visualization for the quantification of boundary layer flow disturbances due to the leading edge condition," Renewable Energy, Elsevier, vol. 138(C), pages 709-721.
    21. López, Javier Contreras & Kolios, Athanasios & Wang, Lin & Chiachio, Manuel, 2023. "A wind turbine blade leading edge rain erosion computational framework," Renewable Energy, Elsevier, vol. 203(C), pages 131-141.
    22. de Oliveira Nogueira, Tiago & Palacio, Gilderlânio Barbosa Alves & Braga, Fabrício Damasceno & Maia, Pedro Paulo Nunes & de Moura, Elineudo Pinho & de Andrade, Carla Freitas & Rocha, Paulo Alexandre C, 2022. "Imbalance classification in a scaled-down wind turbine using radial basis function kernel and support vector machines," Energy, Elsevier, vol. 238(PC).
    23. 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.
    24. Aiman Abbas Mahar & Nayyar Hussain Mirjat & Bhawani S. Chowdhry & Laveet Kumar & Quynh T. Tran & Gaetano Zizzo, 2023. "Condition Assessment and Analysis of Bearing of Doubly Fed Wind Turbines Using Machine Learning Technique," Energies, MDPI, vol. 16(5), pages 1-16, March.
    25. Verma, Amrit Shankar & Jiang, Zhiyu & Caboni, Marco & Verhoef, Hans & van der Mijle Meijer, Harald & Castro, Saullo G.P. & Teuwen, Julie J.E., 2021. "A probabilistic rainfall model to estimate the leading-edge lifetime of wind turbine blade coating system," Renewable Energy, Elsevier, vol. 178(C), pages 1435-1455.

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