Review of criteria for the selection of probability distributions for wind speed data and introduction of the moment and L-moment ratio diagram methods, with a case study

Abstract

This paper reviews the different criteria used in the field of wind energy to compare the goodness-of-fit of candidate probability density functions (pdfs) to wind speed records, and discusses their advantages and disadvantages. The moment ratio and L-moment ratio diagram methods are also proposed as alternative methods for the choice of the pdfs. These two methods have the advantage of allowing an easy comparison of the fit of several pdfs for several time series (stations) on a single diagram. Plotting the position of a given wind speed data set in these diagrams is instantaneous and provides more information than a goodness-of-fit criterion since it provides knowledge about such characteristics as the skewness and kurtosis of the station data set. In this paper, it is proposed to study the applicability of these two methods for the selection of pdfs for wind speed data. Both types of diagrams are used to assess the fit of the pdfs for wind speed series in the United Arab Emirates. The analysis of the moment ratio diagrams reveals that the Kappa, Log-Pearson type III and Generalized Gamma are the distributions that fit best all wind speed series. The Weibull represents the best distribution among those with only one shape parameter. Results obtained with the diagrams are compared with those obtained with goodness-of-fit statistics and a good agreement is observed especially in the case of the L-moment ratio diagram. It is concluded that these diagrams can represent a simple and efficient approach to be used as complementary method to goodness-of-fit criteria.