Accuracy of the modelling is evaluated in terms of Root Mean Square Error (RMSE)
📌 3 Key Takeaways
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Objective & Hypothesis:Wind speed modelling plays a critical role in wind related engineering studies.
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Key Findings & Data:Frequency distribution of wind speed can be displayed different distributions such as Gamma, lognormal, Rayleigh and Weibull.Weibull distribution is used to model of many regions of the world wind speed in recent year.
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Conclusion & Impact:Accuracy of the modelling is evaluated in terms of Root Mean Square Error (RMSE)
Wind speed modelling plays a critical role in wind related engineering studies. Frequency distribution of wind speed can be displayed different distributions such as Gamma, lognormal, Rayleigh and Weibull.Weibull distribution is used to model of many regions of the world wind speed in recent year. In this paper, wind speed potential analysis realized using Inverse Weibull Distribution (IWD) for Bilecik, Turkey. Maximum likelihood method for parameter estimation used for wind speed modelling analysis. All analysis is carried out by Matrix Laboratory (MATLAB) programming language. Monthly and yearly wind speeds are modeled by Inverse Weibull distribution. Accuracy of the modelling is evaluated in terms of Root Mean Square Error (RMSE)
DOKUR, E., KURBAN, M., CEYHAN, S. (2016). WIND SPEED MODELLING USING INVERSE WEIBULL DISTRUBITION: A CASE STUDY FOR BİLECİK, TURKEY. International Journal of Energy Applications and Technologies, Cilt: 3 - Sayı: 2, 55–59. https://ajindex.com/articles/832798