Journal cover Journal topic
Wind Energy Science The interactive open-access journal of the European Academy of Wind Energy
https://doi.org/10.5194/wes-2017-12
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research articles
14 Mar 2017
Review status
A revision of this discussion paper was accepted for the journal Wind Energy Science (WES) and is expected to appear here in due course.
The risks of extreme load extrapolation
Stefan F. van Eijk, René Bos, and Wim A. A. Bierbooms Wind Energy Research Group, Faculty of Aerospace Engineering, Delft University of Technology, 2629 HS Delft, The Netherlands
Abstract. An important problem in wind turbine design is the prediction of the 50-year load, as set by the IEC 61400-1 Design Load Case 1.1. In most cases, designers work with limited simulation budgets and are forced into using extrapolation schemes to obtain the required return level. That this is no easy task is proven by the many studies dedicated to finding the best distribution and fitting method to capture the extreme load behavior as well as possible. However, the issue that is often overlooked is the effect that the sheer uncertainty around the 50-year load has on a design process. In this paper, we use a collection of 96 years' worth of extreme loads to perform a large number of hypothetical design problems. The results show that, even with sample sizes exceeding N = 1,000 ten-minute extremes, designs are often falsely rejected or falsely accepted based on an over- or underpredicted 50-year load. Therefore, designers are advised to be critical of the outcome of DLC 1.1 and should be prepared to invest in large sample sizes.

Citation: van Eijk, S. F., Bos, R., and Bierbooms, W. A. A.: The risks of extreme load extrapolation, Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2017-12, in review, 2017.
Stefan F. van Eijk et al.
Stefan F. van Eijk et al.

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Short summary
Predicting the 50-year extreme loads for wind turbines requires a tremendous computational effort. Therefore, designers often have to extrapolate from relatively small data sets and have to settle for some degree of uncertainty. We investigated the impact of this uncertainty on practical design problems by drawing subsets from a 96-year load data set and using a crude Monte Carlo method to find the 50-year load. The results show that designers have to be careful with selecting sample sizes.
Predicting the 50-year extreme loads for wind turbines requires a tremendous computational...
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