Wind Speed Extreme Quantiles Estimation

Wind speed (WS) probability distribution identification and estimation are the object of an increasing number of studies, especially related to the need of wind energy production evaluation. In this framework, the paper highlights the characterization of extreme WS quantiles, whose values and estimates are very sensitive to the assumed distributional form. This is a crucial issue not only for wind energy production assessment, but also in risk and reliability analysis. For the above purposes, the Lomax model is theoretically deduced and analysed: this model, indeed, well represents the typical "heavy tails" in WS probabilistic distributions arising from field data. A proper Bayes approach for the estimation of both the Lomax survivor function and of the above quantiles is analyzed. A large set of numerical simulations has been performed, and some typical subsets of them are shown to illustrate the efficiency of the estimates, showing excellent results.