Predicting the Extreme Loads on a Wind Turbine Considering Uncertainty in Airfoil Data

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Abstract

The sources contributing to uncertainty in a wind turbine blade static airfoil data include wind tunnel testing, CFD calculations, 3D rotational corrections based on CFD or emprircal models, surface roughness corrections, Reynolds number corrections, expansion to the full 360-degree angle of attack range, validation by full scale measurements, and geometric distortions of the blade during manufacturing and under loading. In this paper a stochastic model of the static airfoil data is proposed to supplement the prediction of extreme loads effects for large wind turbines. It is shown that the uncertainty in airfoil data can have e significant impact on the prediction of extreme loads effects depending on the component, and the correlation along the span of the blade.
Original languageEnglish
Title of host publicationSafety, Reliability, Risk and Life-Cycle Performance of Structures & Infrastructures : Proceedings of the 11th international conference on structural safety and reliability
EditorsGeorge Deodatis, Bruce R. Ellingwood, Dan M. Frangopol
PublisherCRC Press
Publication date2014
Pages215-222
ISBN (Print)978-1-138-00086-5
DOIs
Publication statusPublished - 2014
Event11th International Conference on Structural Safety and Reliability - New York, United States
Duration: 16 Jun 201320 Jun 2013
Conference number: 11

Conference

Conference11th International Conference on Structural Safety and Reliability
Number11
CountryUnited States
CityNew York
Period16/06/201320/06/2013

Keywords

  • Extreme Loads
  • Wind Turbine
  • Airfoil Data

Cite this

Abdallah, I., Natarajan, A., & Sørensen, J. D. (2014). Predicting the Extreme Loads on a Wind Turbine Considering Uncertainty in Airfoil Data. In G. Deodatis, B. R. Ellingwood, & D. M. Frangopol (Eds.), Safety, Reliability, Risk and Life-Cycle Performance of Structures & Infrastructures: Proceedings of the 11th international conference on structural safety and reliability (pp. 215-222). CRC Press. https://doi.org/10.1201/b16387-30