DocumentCode
632288
Title
Wind speed extreme quantiles estimation
Author
Chiodo, Elio
Author_Institution
Dept. of Electr. Eng. & Inf. Technol., Univ. of Naples Federico II, Naples, Italy
fYear
2013
fDate
11-13 June 2013
Firstpage
760
Lastpage
765
Abstract
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.
Keywords
power generation reliability; probability; wind power plants; Bayes approach; Lomax model; Lomax survivor function; WS probability distribution identification; numerical simulation; reliability analysis; risk analysis; wind energy production assessment; wind energy production evaluation; wind speed extreme quantile estimation; wind speed probability distribution identification; Analytical models; Maximum likelihood estimation; Numerical models; Reliability; Wind power generation; Wind speed; Bayes estimation; Gamma distribution; Lomax distribution; Wind Power;
fLanguage
English
Publisher
ieee
Conference_Titel
Clean Electrical Power (ICCEP), 2013 International Conference on
Conference_Location
Alghero
Print_ISBN
978-1-4673-4429-6
Type
conf
DOI
10.1109/ICCEP.2013.6586944
Filename
6586944
Link To Document