Analyzing Winds for Frequency and Duration

Sherlock, R. H.

doi:10.1007/978-1-940033-03-7_9

Cited by 19 publications

(16 citation statements)

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“…On the other hand since Hesselberg and Bjorkdal (1924), we have noticed that the frequency distribution of velocities in turbulent flow obeys the normal law. Recent experimental results, e. g. those by Simmons and Salter (1938), Sherlock (1951) and Frenkiel (1951) gave credence to the normal law. But this law has no reasonable theoretical basis, so that it is adopted as only a hypothesis by these experimenters.…”

Section: Introductionmentioning

confidence: 79%

Frequency Distribution Functions of Velocities in Turbulent Flow

Syõno

1953

Journal of the Meteorological Society of Japan

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-AbstractIn the present article, the frequency distribution function of velocities in turbulent flow is derived by the theory of random walk, on the asumption that the phases of elementary waves are at random and independent with each other. The normal distribution is obtained for the frequency of velocity fluctuations as the first approximation. The second approximation is also obtained. As the number of elementary waves increases, the distribution tends to the normal distribution asymptotically. The frequency distribution of the velocity has a modified form of the noral distribution.

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Section: Introductionmentioning

confidence: 79%

Frequency Distribution Functions of Velocities in Turbulent Flow

Syõno

1953

Journal of the Meteorological Society of Japan

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“…The Gamma pdf is among the earliest statistical distributions that were used in describing the wind behaviors [46]. The Gamma pdf is also known as a Pearson type III pdf [9].…”

Section: Wind Power Density From the Gamma Pdfmentioning

confidence: 99%

Evaluating wind power density models and their statistical properties

Masseran

2015

Energy

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“…The simplest and most practical method for the procedure is to use distribution function [2]. There are several density functions which can be used to describe the wind speed frequency, include for example, the three parameter Weibull distribution [27], the Rayleigh distribution [12] and the gamma distribution [26]. In recent years, most attention has been focused on two parameters Weibull distribution for wind energy applications, not only due to its greater flexibility and simplicity but also because it can provide a good agreement with experimental data [9,22].…”

Section: Statistical Analysis Modelmentioning

confidence: 99%