Bayes Estimation Of Extreme Wind Loads Based Upon A Poisson-Pareto Model

Bayes estimation of extreme load values in the framework of risk and reliability analysis is investigated. The evaluation of extreme values of wind loadings on structures is performed via a combined employment of a Poisson process model for the “peak–over– threshold” characterization and a Pareto distribution for modelling the so-called “parent distribution” which generates the base load values. The method is applied to the extreme wind speed, both for sake of identification and estimation purpose. This topic has indeed brought about an increasing number of studies in the last years, both for wind energy production assessment and also in risk and reliabil ity analysis. This modeling is difficult due to the uncertainty in wind speed probability distributions. For this purpose, the paper proposes a novel Bayes approach for the estimation of the probability that wind speed is lower than a prefixed extreme value. A large set of numerical simulations are performed in the last part of the paper, in order to illustrate the feasibility and efficiency of the above estimation method, especially when compared to the classical Maximum Likelihood method.