The estimation of wind speed extreme values is a topic assuming increasing importance in wind energy studies. Two different methods are compared here for that purpose, in view of safety applications. The first model is a parametric one, based upon a classical extreme value model, such as the Gumbel or the Inverse Weibull distribution. The alternative model is a "non parametric" one, based upon a stochastic characterization of the wind speed by means of a Poisson distribution. For both methods, estimates are carried out by means of Bayes estimation approach. The two approaches are compared in terms of robustness of the estimates of a proper safety index, with respect to departures from the assumed wind speed model. A large set of simulations results are discussed, as a first step towards a deeper insight to wind speed estimation methods, taking into account model uncertainty.
Comparison of two Different Estimation Methods of Wind Speed Extreme Values / Chiodo, Elio; Mazzanti, G.; Karimian, M.; Zoh, R.. - (2015), pp. 653-659. (Intervento presentato al convegno 5th IEEE International Conference on Clean Electrical Power Renewable Energy Resources Impact (ICCEP 2015), tenutosi a Taormina (Italy) nel 16-18 June 2015) [10.1109/ICCEP.2015.7177589].
Comparison of two Different Estimation Methods of Wind Speed Extreme Values
CHIODO, ELIO;
2015
Abstract
The estimation of wind speed extreme values is a topic assuming increasing importance in wind energy studies. Two different methods are compared here for that purpose, in view of safety applications. The first model is a parametric one, based upon a classical extreme value model, such as the Gumbel or the Inverse Weibull distribution. The alternative model is a "non parametric" one, based upon a stochastic characterization of the wind speed by means of a Poisson distribution. For both methods, estimates are carried out by means of Bayes estimation approach. The two approaches are compared in terms of robustness of the estimates of a proper safety index, with respect to departures from the assumed wind speed model. A large set of simulations results are discussed, as a first step towards a deeper insight to wind speed estimation methods, taking into account model uncertainty.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.