Open AccessComparative analysis of methods for modelling the short‐term probability distribution of extreme wind turbine loads
Author(s) -
Dimitrov Nikolay
Publication year - 2016
Publication title -
wind energy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.743
H-Index - 92
eISSN - 1099-1824
pISSN - 1095-4244
DOI - 10.1002/we.1861
Subject(s) - term (time) , turbine , wind power , extreme value theory , environmental science , probability distribution , marine engineering , meteorology , engineering , mathematics , aerospace engineering , statistics , physics , electrical engineering , quantum mechanics
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. Copyright © 2015 John Wiley & Sons, Ltd.