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Methods for Estimating Wind Speed Frequency Distributions

C. G. JustusSchool of Aerospace Engineering, Georgia Institute of Technology, Atlanta 30332

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W. R. HargravesSchool of Aerospace Engineering, Georgia Institute of Technology, Atlanta 30332

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Amir MikhailSchool of Aerospace Engineering, Georgia Institute of Technology, Atlanta 30332

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Denise GraberSchool of Aerospace Engineering, Georgia Institute of Technology, Atlanta 30332

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Abstract

The Weibull function is discussed for representation of the wind speed frequency distribution. Methods are presented for estimating the two Weibull parameters (scale factor c and shape factor k) from simple wind statistics. Comparison is made with a recently proposed method based on the “square-root-normal” distribution with mean wind speed and fastest mile data as input statistics. The Weibull distribution is shown to give smaller root-mean-square errors than the square-root-normal distribution when fitting actual distributions of observed wind speed. Another advantage of the Weibull distribution is the available methodology for projecting to another height the observed Weibull distribution parameters at anemometer height.

Abstract

The Weibull function is discussed for representation of the wind speed frequency distribution. Methods are presented for estimating the two Weibull parameters (scale factor c and shape factor k) from simple wind statistics. Comparison is made with a recently proposed method based on the “square-root-normal” distribution with mean wind speed and fastest mile data as input statistics. The Weibull distribution is shown to give smaller root-mean-square errors than the square-root-normal distribution when fitting actual distributions of observed wind speed. Another advantage of the Weibull distribution is the available methodology for projecting to another height the observed Weibull distribution parameters at anemometer height.

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