Effect of turbulence variation on extreme loads prediction for wind turbines

The effect of varying turbulence levels on long-term loads extrapolation techniques was examined using a joint probability density function of both mean wind speed and turbulence level for loads calculations. The turbulence level has a dramatic effect on the statistics of moment maxima extracted from aeroelastic simulations. Maxima from simulations at lower turbulence levels are more deterministic and become dominated by the stochastic component as turbulence level increases. Short-term probability distributions were calculated using four different moment-based fitting methods. Several hundred of these distributions were used to calculate a long-term probability function. From the long-term probability, 1- and 50-yr extreme loads were estimated. As an alternative, using a normal conditional distribution of turbulence level produced a long-term load comparable to that of a log-normal conditional distribution and may be more straightforward to implement. A parametric model of the moments was also used to estimate the extreme loads. The parametric model required less data, but predicted significantly lower loads than the empirical model. An input extrapolation technique was also examined. Extrapolating the turbulence level prior to input into the aeroelastic code simplifies the loads extrapolation procedure but, in this case, produces loads lower than most empirical models and may be non-conservative in general.