Araştırma Makalesi
BibTex RIS Kaynak Göster

Five different distributions and metaheuristics to model wind speed distribution

Yıl 2021, Cilt: 7 Sayı: Supp 14, 1898 - 1920, 30.12.2021
https://doi.org/10.18186/thermal.1051262

Öz

This paper presents a comprehensive empirical study of five distribution functions to analyze wind energy potential: Rayleigh, Weibull, Gamma, Burr Type XII, and Generalized Extreme Value. In addition, two metaheuristics optimization methods, Grey Wolf optimization and Whale optimization algorithm, are utilized to determine the optimal parameter values of each distribution. Five error measures are investigated and compared to test the accuracy of the introduced distributions and optimization methods, such as mean absolute error, root mean square error, regression coefficient, correlation coefficient, and net fitness. The Catalca site in Istanbul, Turkey, was selected to be the case study to conduct this analysis. The obtained results confirm that all introduced distributions based on optimization methods efficiently model wind speed distribution in the selected site. Although Gamma distribution based on GWO and WOA outperformed other distributions for all datasets at all heights, it was the worst in terms of computation complexity. Rayleigh distribution occupied the latest rank, but it was the best in terms of computation complexity. MATLAB 2020b and Excel 365 were used to perform this study.

Kaynakça

  • The article references can be accessed from the .pdf file.
Yıl 2021, Cilt: 7 Sayı: Supp 14, 1898 - 1920, 30.12.2021
https://doi.org/10.18186/thermal.1051262

Öz

Kaynakça

  • The article references can be accessed from the .pdf file.
Toplam 1 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Termodinamik ve İstatistiksel Fizik
Bölüm Makaleler
Yazarlar

Mohammed Wadı 0000-0001-8928-3729

Yayımlanma Tarihi 30 Aralık 2021
Gönderilme Tarihi 6 Şubat 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 7 Sayı: Supp 14

Kaynak Göster

APA Wadı, M. (2021). Five different distributions and metaheuristics to model wind speed distribution. Journal of Thermal Engineering, 7(Supp 14), 1898-1920. https://doi.org/10.18186/thermal.1051262
AMA Wadı M. Five different distributions and metaheuristics to model wind speed distribution. Journal of Thermal Engineering. Aralık 2021;7(Supp 14):1898-1920. doi:10.18186/thermal.1051262
Chicago Wadı, Mohammed. “Five Different Distributions and Metaheuristics to Model Wind Speed Distribution”. Journal of Thermal Engineering 7, sy. Supp 14 (Aralık 2021): 1898-1920. https://doi.org/10.18186/thermal.1051262.
EndNote Wadı M (01 Aralık 2021) Five different distributions and metaheuristics to model wind speed distribution. Journal of Thermal Engineering 7 Supp 14 1898–1920.
IEEE M. Wadı, “Five different distributions and metaheuristics to model wind speed distribution”, Journal of Thermal Engineering, c. 7, sy. Supp 14, ss. 1898–1920, 2021, doi: 10.18186/thermal.1051262.
ISNAD Wadı, Mohammed. “Five Different Distributions and Metaheuristics to Model Wind Speed Distribution”. Journal of Thermal Engineering 7/Supp 14 (Aralık 2021), 1898-1920. https://doi.org/10.18186/thermal.1051262.
JAMA Wadı M. Five different distributions and metaheuristics to model wind speed distribution. Journal of Thermal Engineering. 2021;7:1898–1920.
MLA Wadı, Mohammed. “Five Different Distributions and Metaheuristics to Model Wind Speed Distribution”. Journal of Thermal Engineering, c. 7, sy. Supp 14, 2021, ss. 1898-20, doi:10.18186/thermal.1051262.
Vancouver Wadı M. Five different distributions and metaheuristics to model wind speed distribution. Journal of Thermal Engineering. 2021;7(Supp 14):1898-920.

IMPORTANT NOTE: JOURNAL SUBMISSION LINK http://eds.yildiz.edu.tr/journal-of-thermal-engineering