Articles | Volume 3, issue 2
Wind Energ. Sci., 3, 475–487, 2018
https://doi.org/10.5194/wes-3-475-2018
Wind Energ. Sci., 3, 475–487, 2018
https://doi.org/10.5194/wes-3-475-2018
Research article
11 Jul 2018
Research article | 11 Jul 2018

Adaptive stratified importance sampling: hybridization of extrapolation and importance sampling Monte Carlo methods for estimation of wind turbine extreme loads

Peter Graf et al.

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Latest update: 28 Sep 2022
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Short summary
Current approaches to wind turbine extreme load estimation are insufficient to routinely and reliably make required estimates over 50-year return periods. Our work hybridizes the two main approaches and casts the problem as stochastic optimization. However, the extreme variability in turbine response implies even an optimal sampling strategy needs unrealistic computing resources. We therefore conclude that further improvement requires better understanding of the underlying causes of loads.