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The Suitable Statistical Model Selection for the Wind Speed of Tabriz and Orumiyeh Stations
Meysam Mohammadpour , Hossein Bevrani, Reza Arabi Belaghi
Abstract:   (472 Views)
Wind speed probabilistic distributions are one of the main wind characteristics for the evaluation of wind energy potential in a specific region.  In this paper, 3-parameter Log-Logistic distribution is introduced and it compared with six used statistical models for the modeling the actual wind speed data reported of Tabriz and Orumiyeh stations in Iran. The maximum likelihood estimators method via Nelder–Mead algorithm is utilized for estimating the model parameters. The flexibility of proposed distributions is measured according to the coefficient of determination, Chi-square test, Kolmogorov-Smirnov test, and root mean square error criterion. Results of the analysis show that 3-parameter Log-Logistic distribution provides the best fit to model the annual and seasonal wind speed data in Orumiyeh station and except summer season for Tabriz station. Also, wind power density error is estimated for the proposed different distributions.
Keywords: Wind Speed, Empirical Distribution, Maximum Likelihood Method, Goodness-of-fit Tests, Wind Power Density Error.
Full-Text [PDF 4454 kb]   (4 Downloads)    
Type of Study: Applied | Subject: Applied Statistics
Received: 2019/12/1 | Accepted: 2021/02/28 | Published: 2021/09/1
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مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences
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