Bayes estimation of Inverse Weibull distribution for extreme wind speed prediction

Abstract

Prediction of extreme values of wind speed is a key issue for both wind energy and wind tower safety assessment. The paper proposes a new method for such estimation, in the framework of safety assessment under extreme wind speed, based upon an adequate probabilistic model. The method assumes an Inverse Weibull probability distribution for the characterization of extreme wind speeds, and is developed by means of a novel Bayes estimation method. Such method uses a prior assessment of a given quantile of the wind speed by means of a “Negative LogLognormal” distribution. In the paper, by means of large set of numerical simulations relevant to typical wind speed data, the efficiency of the Bayes methods is discussed. Attention is focused in particular on the robustness of the estimates with respect to departures from the assumed wind speed probability distributions, assuming the Gumbel distribution as an alternative extreme value model.