Comparative analysis of methods for modelling the short-term probability distribution of extreme wind turbine loads

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Abstract

We have tested the performance of statistical extrapolation methods in predicting the extreme response of a multi-megawatt wind turbine generator. We have applied the peaks-over-threshold, block maxima and average conditional exceedance rates (ACER) methods for peaks extraction, combined with four extrapolation techniques: the Weibull, Gumbel and Pareto distributions and a double-exponential asymptotic extreme value function based on the ACER method. For the successful implementation of a fully automated extrapolation process, we have developed a procedure for automatic identification of tail threshold levels, based on the assumption that the response tail is asymptotically Gumbel distributed. Example analyses were carried out, aimed at comparing the different methods, analysing the statistical uncertainties and identifying the factors, which are critical to the accuracy and reliability of the extrapolation. The present paper describes the modelling procedures and makes a comparison of extrapolation methods based on the results from the example calculations.
Original languageEnglish
JournalWind Energy
Volume19
Issue number4
Pages (from-to)717–737
Number of pages21
ISSN1095-4244
DOIs
Publication statusPublished - 2016

Keywords

  • Extrapolation
  • Wind turbine
  • Loads
  • Probability
  • Short-term
  • Extreme
  • Load extrapolation

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