Abstract
The wind energy potential of a specified area can be estimated using wind speed distribution. In this study, the selection of probability density functions is used to model wind speed data recorded at two stations in Pakistan. The suitability of fitted distributions is evaluated using the goodness of fit criterion, power density error, log-likelihood, root mean square error, coefficient of determination, AIC, and BIC. The wind speed data are obtained from two coastal regions of Pakistan at 10m/s average rate for session 2017-2018. Findings indicated that the extended generalized Lindley distribution provide generally the best fit to the wind speed data for both stations. However, it is also observed that power Lindley and extended generalized Lindley distributions have better performance based on power density error criteria in Gwadar and Haripur, respectively.
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