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Impact of meteorological data factors and material characterization method on the predictions of leading edge erosion of wind turbine blades

Author

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  • Castorrini, Alessio
  • Barnabei, Valerio F.
  • Domenech, Luis
  • Šakalyté, Asta
  • Sánchez, Fernando
  • Campobasso, M. Sergio

Abstract

Leading edge erosion of wind turbine blades is a major contributor to wind farm energy yield losses and maintenance costs. Presented is a multidisciplinary framework for predicting rain erosion lifetimes of wind turbine blades. Key aim is assessing the sensitivity of lifetime predictions to: modeling aspects (material erosion model, blade aerodynamics), input data and/or their preprocessing (joint frequency distribution of wind speed and droplet size based on synchronous site-specific measurements versus frequency distribution generated with partly site-agnostic modeling standards, wind speed records of nacelle anemometer or extrapolated at hub height from met masts), and environmental conditions (UV weathering). The analyses consider a Northwest England onshore site where a utility-scale turbine is operational, focus on a reference 5 MW turbine assumed operational at the site, and use a typical leading edge coating material. It is found that the largest variations in erosion lifetime predictions are due to material erosion model (based on rain erosion test data or fundamental material properties) and wind and rain model (measurement-based joint wind speed and droplet size distribution or standard-based modeled distribution). The use of joint wind and rain distribution also enables identifying wind/rain states with highest erosion potential, knowledge paramount to deploying erosion-safe turbine control.

Suggested Citation

  • Castorrini, Alessio & Barnabei, Valerio F. & Domenech, Luis & Šakalyté, Asta & Sánchez, Fernando & Campobasso, M. Sergio, 2024. "Impact of meteorological data factors and material characterization method on the predictions of leading edge erosion of wind turbine blades," Renewable Energy, Elsevier, vol. 227(C).
  • Handle: RePEc:eee:renene:v:227:y:2024:i:c:s0960148124006141
    DOI: 10.1016/j.renene.2024.120549
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    References listed on IDEAS

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    1. Fred Letson & Sara C. Pryor, 2023. "From Hydrometeor Size Distribution Measurements to Projections of Wind Turbine Blade Leading-Edge Erosion," Energies, MDPI, vol. 16(9), pages 1-29, May.
    2. Slot, H.M. & Gelinck, E.R.M. & Rentrop, C. & van der Heide, E., 2015. "Leading edge erosion of coated wind turbine blades: Review of coating life models," Renewable Energy, Elsevier, vol. 80(C), pages 837-848.
    3. 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.
    4. 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.
    5. 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).
    6. Alessio Castorrini & Paolo Venturini & Aldo Bonfiglioli, 2022. "Generation of Surface Maps of Erosion Resistance for Wind Turbine Blades under Rain Flows," Energies, MDPI, vol. 15(15), pages 1-14, August.
    7. Bech, Jakob Ilsted & Johansen, Nicolai Frost-Jensen & Madsen, Martin Bonde & Hannesdóttir, Ásta & Hasager, Charlotte Bay, 2022. "Experimental study on the effect of drop size in rain erosion test and on lifetime prediction of wind turbine blades," Renewable Energy, Elsevier, vol. 197(C), pages 776-789.
    8. Castorrini, Alessio & Ortolani, Andrea & Campobasso, M. Sergio, 2023. "Assessing the progression of wind turbine energy yield losses due to blade erosion by resolving damage geometries from lab tests and field observations," Renewable Energy, Elsevier, vol. 218(C).
    9. Sara C. Pryor & Rebecca J. Barthelmie & Jeremy Cadence & Ebba Dellwik & Charlotte B. Hasager & Stephan T. Kral & Joachim Reuder & Marianne Rodgers & Marijn Veraart, 2022. "Atmospheric Drivers of Wind Turbine Blade Leading Edge Erosion: Review and Recommendations for Future Research," Energies, MDPI, vol. 15(22), pages 1-41, November.
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