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

Wind Speed Potential Analysis Based on Weibull Distribution

Emrah Dokur
Mehmet Kurban
Pages
231–235
Publication Date
2015-12-30
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

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

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Weibull probability density function used to determine the wind energy potential commonly.
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Key Findings & Data: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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Conclusion & Impact:Accuracy of the modeling is evaluated in terms of Root Mean Square Error (RMSE).
🔬Design:Modeling & Simulation
📍Scope:2010-2014 Verileri
⚙️Variables: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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Cite This Article

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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References (9)

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