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Dergiler / Balkan Journal of Electrical and Computer Engineering / 2015 / Cilt: 3 Özel Sayı

Wind Speed Potential Analysis Based on Weibull Distribution

Emrah Dokur
Mehmet Kurban
Sayfa
231–235
Yayın Tarihi
2015-12-30
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Accuracy of the modeling is evaluated in terms of Root Mean Square Error (RMSE).

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Weibull probability density function used to determine the wind energy potential commonly.
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Temel Bulgular & Veri:In this paper, wind energy potential of Bilecik region is analyzed statistically by using the Turkish State Meteorological Service’s hourly wind speed data between 2010-2014 measured in Bilecik meteorological station.
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Sonuç & Katkı:Accuracy of the modeling is evaluated in terms of Root Mean Square Error (RMSE).
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:2010-2014 Verileri
⚙️Değişkenler:Weibull Distribution · Wind Speed · Energ

Abstract

Weibull probability density function used to determine the wind energy potential commonly. In this paper, wind energy potential of Bilecik region is analyzed statistically by using the Turkish State Meteorological Service’s hourly wind speed data between 2010-2014 measured in Bilecik meteorological station. It is used the two- parameter Weibull to determine wind energy potential of the region. The parameters of the Weibull distributions used for finding the estimation of average speed, standard deviation, and power density is found by using the Maximum likelihood method. All analysis is carried out by Matrix Laboratory (MATLAB) programming language. Monthly and yearly wind speeds are modeled by Weibull distribution statistically. Accuracy of the modeling is evaluated in terms of Root Mean Square Error (RMSE).

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Bu Makaleye Atıf Yap

Dokur, E., Kurban, M. (2015). Wind Speed Potential Analysis Based on Weibull Distribution. Balkan Journal of Electrical and Computer Engineering, Cilt: 3 Özel Sayı, 231–235. https://ajindex.com/articles/1373414

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Kaynakça (9)

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  2. Kurban, M., Hocaoğlu, F. O., & Kantar, Y. M. (2011). Rüzgar Enerjisi Potansiyelinin Tahmininde Kullanılan İki Farklı İstatistiksel Dağılımın Karşılaştırmalı Analizi. Pamukkale University Journal Of Engineering Sciences, 13(1)
  3. Akdağ, S. A., & Güler, Ö. (2008) Weibull Dağılım Parametrelerini Belirleme Metodlarının Karşılaştırılması. VII. Ulusal Temiz Enerji Sempozyumu, UTES’2008 17-19 Aralık 2008, İstanbul,707-714
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  5. Yıldırım, U., Gazibey, Y., & Güngör, A. (2012). Niğde İli Rüzgar Enerjisi Potansiyeli. Mühendislik Bilimleri Dergisi, 1(2), 37-47
  6. Akdağ, S. A., & Dinler, A. (2009). A New Method To Estimate Weibull Parameters For Wind Energy Applications. Energy Conversion And Management, 50(7), 1761-1766
  7. Cheng, R. C. H., & Amin, N. A. K. (1983). Estimating parameters in continuous univariate distributions with a shifted origin. Journal of the Royal Statistical Society. Series B (Methodological), 394-403
  8. Patel, M. R. (2005). Wind and solar power systems: design, analysis, and operation. CRC press
  9. Stevens, M. J. M., & Smulders, P. T. (1979). The estimation of the parameters of the Weibull wind speed distribution for wind energy utilization purposes. Wind engineering, 3, 132-145