Probability Modeling of Monthly Maximum Sustained Wind Speed in Bangladesh
AbstractWind speed is one the most important parameter of wind energy. However, the probability density functions (pdfs) are usually used to describe the characteristics of wind speed. In literature, several pdfs have been investigated to justify the suitability of modeling the wind speed in different regions all over the world. Therefore, the choice of the pdf is very crucial. This paper, firstly finds the estimates of the parameters of all probability distribution considered in this study to describe wind speed characteristics by using the maximum likelihood method and iterations were carried out with Newton-Raphson technique. Finally, the appropriate pdf for monthly maximum sustained wind speed at Cox’s Bazar in Bangladesh is selected with the help of the Kolmogorov–Smirnov statistic, the coefficient of determination , the Chi-square statistic, Root mean square error (RMSE), AIC and BIC. Here, results depict that, among the distributions considered in this study, the Skewed t (ST) distribution provides the best fit to the wind speed data.
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