The Weibull distribution function was found to be more appropriate than the Rayleigh distribution function.
📌 3 Key Takeaways
🎯
Objective & Hypothesis:In this study, the statistical analysis of wind power density and wind speed distribution parameters in İskenderun was investigated using the hourly wind speed data measured by the General Directorate of Meteorology between 2005 and 2014.
📊
Key Findings & Data:Weibull and Rayleigh distributions were used for modeling and the success of this modeling process was evaluated according to the parameters of R2, RMSE and c2.
💡
Conclusion & Impact:The Weibull distribution function was found to be more appropriate than the Rayleigh distribution function.
🔬Design:Modeling & Simulation
📍Scope:2005 Verileri
⚙️Variables:Wind energy · Statistically analysis of the wind energy potential · Weibull distribution
Abstract
In this study, the statistical analysis of wind power density and wind speed distribution parameters in İskenderun was investigated using the hourly wind speed data measured by the General Directorate of Meteorology between 2005 and 2014. Weibull and Rayleigh distributions were used for modeling and the success of this modeling process was evaluated according to the parameters of R2, RMSE and c2. The result of the study showed that Iskenderun has a mean wind speed of 2.82 m/s with a maximum value of 4.5 m/s in July of 2006 and a minimum value of 1.68 m/s in November of 2012 while the corresponding mean wind power density is approximately 19.16 W/m2 for the whole year. The Weibull distribution function was found to be more appropriate than the Rayleigh distribution function.
AKPINAR, E. (2018). STATISTICAL ANALYSIS OF WIND SPEED DISTRIBUTION BASED ON WEIBULL AND RAYLEIGH METHODS OF ISKENDERUN-TURKEY. European Journal of Technique, Cilt: 8 - Sayı: 1, 17–34. https://ajindex.com/articles/201856
Ali Naci Çelik E-mail address: [email protected] (A.N. Celik). E. Dokur, Electrical and Electronics Engineering Department, Bilecik S.E. University, Bilecik, Turkey, (e-mail: [email protected]). K. Ulgen, Solar Energy Institute, Ege University, 35100 Bornova, Izmir, Turkey. E-mail: [email protected]