:: Volume 15, Issue 1 (9-2021) ::
JSS 2021, 15(1): 219-232 Back to browse issues page
The Suitable Statistical Model Selection for the Wind Speed of Tabriz and Orumiyeh Stations
Meysam Mohammadpour * , Hossein Bevrani , Reza Arabi Belaghi
Abstract:   (3635 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 267 kb]   (1026 Downloads)    
Type of Study: Applied | Subject: Applied Statistics
Received: 2019/12/1 | Accepted: 2021/02/28 | Published: 2021/09/1



XML   Persian Abstract   Print



Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 15, Issue 1 (9-2021) Back to browse issues page