During the design phase of an offshore wind turbine, it is required to assess the impact of loads on the turbine life time. Due to the varying environmental conditions, the effect of various uncertain parameters has to be studied to provide meaningful conclusions. Incorporating such uncertain parameters in this regard is often done by applying binning, where the probability density function under consideration is binned and in each bin random simulations are run to estimate the loads. A different methodology for quantifying uncertainties proposed in this work is polynomial interpolation, a more efficient technique that allows to more accurately predict the loads on the turbine for specific load cases. This efficiency is demonstrated by applying the technique to a power production test problem and to IEC Design Load Case 1.1, where the ultimate loads are determined using BLADED. The results show that the interpolating polynomial is capable of representing the load model. Our proposed surrogate modeling approach therefore has the potential to significantly speed up the design and analysis of offshore wind turbines by reducing the time required for load case assessment.

Journal of Physics: Conference Series
Excellence in Uncertainty Reduction of Offshore Wind Systems (uitgewerkt programmavoorstel)
The Science of Making Torque from Wind
Centrum Wiskunde & Informatica, Amsterdam (CWI), The Netherlands

van den Bos, L.M.M, Sanderse, B, Blonk, L, Bierbooms, W.A.A.M, & van Bussel, G.J.W. (2018). Efficient ultimate load estimation for offshore wind turbines using interpolating surrogate models. In Modeling and Simulation Technology. doi:10.1088/1742-6596/1037/6/062017