Analysis of Wind Speed Distribution: Comparative Study of Weibull to Rayleigh Probability Density Function; A Case of Two Sites in Ethiopia
American Journal of Modern Energy
Volume 2, Issue 3, June 2016, Pages: 10-16
Received: Jun. 30, 2016;
Accepted: Jul. 28, 2016;
Published: Aug. 26, 2016
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Girma Dejene Nage, Department of Physics, College of Natural and Computational Sciences, Mizan-Tepi University, Tepi, Ethiopia
This study is primarily aimed to estimate the wind speed distribution of the location, Dire Dawa and Hawasa. Wind speed is the most important parameter in the analysis of wind energy resource, design and study of wind energy conversion systems. In this study, statistical methods were used to analyze wind speed data of Dire Dawa and Hawasa. Based on these data, the shape, k and scale, c parameters of the two locations were determined. The monthly mean values of k range from 1.86 to 8.19, with yearly mean value of 4.46, while c is in the range of 1.60 to 3.65 m/s with yearly mean value of 2.59 m/s for Dire Dawa and monthly mean values of k range from 2.00 to 2.79, with yearly mean value of 2.38, while c is in the range of 1.50 to 2.19 m/s with yearly mean value of 1.76 m/s for Hawasa. Two probability density functions are fitted to the measured probability distributions on a monthly basis. From statistical analysis of distributions, the Weibull distribution is better in fitting the measured probability density distributions than the Rayleigh distribution for the whole year. The cumulative probability distribution indicates, the probability for which the wind blows with a monthly mean wind speed v is equal or lower than 5 m/s is almost one.
Girma Dejene Nage,
Analysis of Wind Speed Distribution: Comparative Study of Weibull to Rayleigh Probability Density Function; A Case of Two Sites in Ethiopia, American Journal of Modern Energy.
Vol. 2, No. 3,
2016, pp. 10-16.
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