Analysis of wind speed distributions: Wind distribution function derived from minimum cross entropy principles as better alternative to Weibull function

The demand for electricity in Malaysia is growing in tandem with its Gross Domestic Product (GDP) growth. Malaysia is going to need even more energy as it strives to grow towards a high-income economy. Malaysia has taken steps to exploring the renewable energy (RE) including wind energy as an alternative source for generating electricity. In the present study, the wind energy potential of the site is statistically analyzed based on 1-year measured hourly time-series wind speed data. Wind data were obtained from the Malaysian Meteorological Department (MMD) weather stations at nine selected sites in Malaysia. The data were calculated by using the MATLAB programming to determine and generate the Weibull and Rayleigh distribution functions. Both Weibull and Rayleigh models are fitted and compared to the Field data probability distributions of year 2011. From the analysis, it was shown that the Weibull distribution is fitting the Field data better than the Rayleigh distribution for the whole year 2011. The wind power density of every site has been studied based on the Weibull and Rayleigh functions. The Weibull distribution shows a good approximation for estimation of wind power density in Malaysia.

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“…Kantar and Usta (2008) has discussed, the most common equation used for the variation of wind speed with height is the power law as follows;…”

Section: Vertical Extrapolation Of Wind Speedmentioning

confidence: 99%

Statistical Analysis of Wind Power Density Based on the Weibull and Rayleigh Models of Selected Site in Malaysia

Albani

Ibrahim

2014

Pak.j.stat.oper.res.

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“…The cumulative distribution function (cdf) of the Weibull random variable, widely-used in engineering fields [1,21,22] is given as follows:…”

Section: Lse Methods For Log-logistic and Weibull Distributionsmentioning

confidence: 99%

Estimating Variances in Weighted Least-Squares Estimation of Distributional Parameters

Kantar

2016

MCA

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Many estimation methods have been proposed for the parameters of statistical distribution. The least squares estimation method, based on a regression model or probability plot, is frequently used by practitioners since its implementation procedure is extremely simple in complete and censoring data cases. However, in the procedure, heteroscedasticity is present in the used regression model and, thus, the weighted least squares estimation or alternative methods should be used. This study proposes an alternative method for the estimation of variance, based on a dependent variable generated via simulation, in order to estimate distributional parameters using the weighted least squares method. In the estimation procedure, the variances or weights are expressed as a function of the rank of the data point in the sample. The considered weighted estimation method is evaluated for the shape parameter of the log-logistic and Weibull distributions via a simulation study. It is found that the considered weighted estimation method shows better performance than the maximum likelihood, least-squares, and certain other alternative estimation approaches in terms of mean square error for most of the considered sample sizes. In addition, a real-life example from hydrology is provided to demonstrate the performance of the considered method.

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“…It is well known that the power of the wind energy depends on wind velocity`v', blade swept area of wind turbine`A', and air density of region`'; plus, the power of wind energy is given in the following equation [10]:…”

Section: Statistical Analysis Of Wind Energymentioning

confidence: 99%

“…We have collected the ve-year data of the wind speed measured at 10-meter height from the General Directorate of State Meteorology. Kantar and Usta [10] analyzed the use of the minimum cross entropy principle in the estimation of wind speed distribution and wind power density functions. Moreover, they compared the Weibull pdf (probability density function) with the MinxEnt (minimum cross-entropy principle) pdfs.…”

Section: Introductionmentioning

confidence: 99%

Determination of Weibull Parameters by Different Numerical Methods and Analysis of Wind Power Density in Osmaniye, Turkey

Kaplan

2017

Scientia Iranica

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Abstract. In this study, the potential of wind energy in Osmaniye Region has been analysed statistically on the basis of information that has been measured hourly between the years 2009 to 2013. The two-parameter Weibull Distribution Function is generally applied to evaluate the potential of wind energy in any region. This study introduced the evaluation of Weibull Distribution Function parameters which are obtained by di erent kinds of numerical methods, namely Graphical Method (GM), Moment Method (MM), Energy Pattern Method (EPM), Energy Trend Method (ETM), and Maximum Likelihood Method (MLM). The Relative Percentage Error (RPE) of statistical test is used to compare the e ciency of all used methods. The calculated power density of all used numerical methods is a major key issue for suitability use of wind energy. The evaluation of Weibull parameters and wind power distribution play a crucial role in producing electricity from wind power. The results of the used methods are compared, and the obtained pre-research results show that the wind energy potential in Osmaniye Region is statistically suitable for electricity production.

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Analysis of wind speed distributions: Wind distribution function derived from minimum cross entropy principles as better alternative to Weibull function

Cited by 77 publications

References 21 publications

Statistical Analysis of Wind Power Density Based on the Weibull and Rayleigh Models of Selected Site in Malaysia

Statistical Analysis of Wind Power Density Based on the Weibull and Rayleigh Models of Selected Site in Malaysia

Estimating Variances in Weighted Least-Squares Estimation of Distributional Parameters

Determination of Weibull Parameters by Different Numerical Methods and Analysis of Wind Power Density in Osmaniye, Turkey

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