Statistical load extrapolation is required to predict long-term extreme loads for offshore as well as onshore wind turbines, as per design standards from the International Electrotechnical Commission (IEC). Load extrapolation involves three major steps: first, extracting load extremes from simulated time series of turbine loads; then, fitting “short-term” probability distributions to these extremes for a given environmental state; and finally, integrating short-term distributions over all environmental states to develop a “long-term” distribution from which the long-term load associated with a desired return period is obtained. Several different techniques are available for each of the three steps. The IEC design standards do not provide any guidelines regarding which techniques are suitable for accurate prediction of long-term loads. We present a review of various extrapolation techniques for offshore wind turbines. We use a 5MW utility-scale offshore wind turbine model (developed at the National Renewable Energy Laboratory) with a monopile support structure for stochastic time-domain simulations. From ten-minute simulations, we extract extremes using the global maxima method, the peak-over-threshold method, and the block maxima method. Using a convergence criterion for short-term distributions, we show that it is more important to carry out an adequate number of simulations than to extract more extremes from each ten-minute simulation. We show that the inverse first-order reliability method can be as accurate but more efficient than the direct integration method to estimate long-term loads.
Agarwal, P. and Manuel, L., “Load Extrapolation Methods for Offshore Wind Turbines,” Special Session on Offshore Wind Energy, Offshore Technology Conference, Houston, TX, May 2010.
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