Effects of finite sampling on fatigue damage estimation of wind turbine components: A statistical study

Author:

Mozafari Shadan1ORCID,Dykes Katherine1,Rinker Jennifer Marie1,Veers Paul2

Affiliation:

1. Department of Wind and Energy Systems, Risø, Roskilde, Denmark

2. National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO, USA

Abstract

The variability of the wind turbine loads complicates fatigue assessment in the design phase, as performing simulations covering the entire lifetime is computationally expensive. The current work provides important information for assessing the uncertainty in fatigue damage estimation due to finite data. We study the sample size effect on mean, variance, and skewness of damage in each wind bin, identify the important wind bins, and study the uncertainty propagation from each wind bin to the lifetime damage using 3600 aeroelastic simulations and bootstrapping. To achieve less than 1% error in the damage estimation across all load channels in the current case study, at least 100 turbulence seeds are needed. Damage in different wind bins follows a lognormal distribution when using the conventional approach of six seeds. The provided insights and information allow the designer to achieve a specific level of accuracy for a given computational cost using strategic bin sampling.

Publisher

SAGE Publications

Subject

Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment

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