Statistical analysis of wind speed data

Author

Teyabeen, Alhassan Ali

Author_Institution

Dept. of Electr. & Electron. Eng., Center for Solar Energy Res. & Studies, Tripoli, Libya

fYear

2015

fDate

24-26 March 2015

Firstpage

1

Lastpage

6

Abstract

The main objective of this paper is to analyze the statistical wind speed data recorded in Zuwara-Libya during 2007, the wind speed measured at three hub heights of 10m, 30m, and 50m above the ground, wind speeds was taken every 1 minute, were averaged over 10 minutes. The wind speed data set is analyzed using Weibull, Rayleigh, and Gamma distribution. An effort has been made to find out the best fitting distribution of wind speed data, which are evaluated by using two goodness of fit tests, namely, Chi-Squared test, and Kolmgorov-Smirnov test. Root mean square error, and correlation coefficient are also used to determine error and describe the correlation between the observed data and each distribution. From analysis it is concluded that the Weibull distribution gives the best fitting for observed wind speed.

Keywords

Weibull distribution; gamma distribution; least mean squares methods; statistical analysis; wind power; Kolmgorov-Smirnov test; Rayleigh distribution; Weibull distribution; chi-squared test; correlation coefficient; gamma distribution; root mean square error; statistical analysis; statistical wind speed data; Correlation; Correlation coefficient; Distribution functions; Probability density function; Standards; Weibull distribution; Wind speed; Chi-Squared Kolmogorov-Smirnov test; Gamma distribution; Rayleigh; Weibull; Wind speed; correlation; cumulative distribution function; goodness of fit; probability density function; root mean square error;

fLanguage

English

Publisher

ieee

Conference_Titel

Renewable Energy Congress (IREC), 2015 6th International

Conference_Location

Sousse

Type

conf

DOI

10.1109/IREC.2015.7110866

Filename

7110866