Determination of Weibull parameters with using Standard Deviation Method and performance comparison at different locations

Kaplan, Yusuf Alper

doi:10.24200/sci.2019.50323.1632

Cited by 3 publications

(7 citation statements)

References 24 publications

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“…In this method, the gamma function is employed to nd the value of parameter c. Determination of parameters `k' and `c' is expressed in Eqs. ( 7) and ( 8) [2,32,40]:…”

Section: Empirical Methods (Em)mentioning

confidence: 99%

“…Scale parameter \c" is directly related to the average wind speed. The large \c" indicates that the average wind speed is high [2,36,37]. The frequency distribution of the wind speed in di erent ranges is shown in Figure 5.…”

Section: Weibull Distribution Function (Wdf)mentioning

confidence: 99%

“…In this study, three di erent statistical error analysis tests were employed to compare the performance of the methods used. The general equations of these statistical error analysis tests are given in the following equations [2,32]:…”

Section: Statistical Error Analysismentioning

confidence: 99%

“…The results were evaluated statistically using three di erent statistical error analysis tests. In the table, the performances of the methods utilized to nd the coe cients of WDF are compared in detail [2].…”

Section: Mean Percentage Error (Mpe)mentioning

confidence: 99%

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The investigation of the compliance of offshore wind data with the Weibull distribution function with using six different methods

Kaplan

2022

Scientia Iranica

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The aim of this study is to investigate how the Weibull Distribution Function (WDF) is compatible with the wind data in o shore regions. Many academic studies on wind energy have been conducted. Determining potential o shore wind energy and making investments in this area have gained further signi cance today. Although many studies have been made on wind energy, o shore wind energy has received less attention. The compatibility between wind data and WDF on land has been investigated by many academic studies, and the results have been evaluated. However, the compatibility of the o shore wind data with the WDF has not been investigated su ciently and there are steps to be taken in this regard. In this study, a point was selected in Iskenderun Gulf to examine the compatibility of o shore wind data with WDF function. This study determined both the wind energy potential of the selected region and made many contributions to the literature. Six di erent methods were used to determine the parameters of the WDF and then, their performance were evaluated in di erent statistical error analysis tests.

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“…In this method, the gamma function is employed to nd the value of parameter c. Determination of parameters `k' and `c' is expressed in Eqs. ( 7) and ( 8) [2,32,40]:…”

Section: Empirical Methods (Em)mentioning

confidence: 99%

Section: Weibull Distribution Function (Wdf)mentioning

confidence: 99%

Section: Statistical Error Analysismentioning

confidence: 99%

Section: Mean Percentage Error (Mpe)mentioning

confidence: 99%

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The investigation of the compliance of offshore wind data with the Weibull distribution function with using six different methods

Kaplan

2022

Scientia Iranica

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“…The power of the sea current that flows at velocity v through a turbine-swept area A increases as the cube of its velocity, and it is calculated as follows [34,35]:…”

Section: Power Potential Of Sea Current Velocitymentioning

confidence: 99%

Statistical characteristics, probability distribution, and power potential of sea water velocity in Turkey

Yıldırım

2022

European Mechanical Science

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Sea currents have the potential to supply electricity from a renewable energy source to coastal regions. The assessment of the potential energy that could be generated is the first step toward developing this resource. In this study, the data was collected at 5 m and 35 m depths below the sea surface level, including sea current velocity and direction. A detailed field measurement, of the probability of sea water velocity at three stations (Antalya, Silivri, Istanbul) for 5 months is carried out. The sea current power density values in these stations were 10.41, 4.92, and 7.91 W/m2 at 5 m depth, respectively. Besides, average sea current power density values were seen to be closely arranged with 11.44, 4.07, and 9.06 W/m2 at 35 depths, respectively. In addition, statistical analysis applying Weibull and Rayleigh models is also presented. It is shown that the use of a Weibull probability distribution facilitates the analysis of sea velocity conditions and is also able to predict the power density with a high degree of accuracy. The results of this study are useful for the understanding of marine hydrodynamics of these areas, where sea current power projects may be started in Turkey.

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Wind Energy Assessment Using Weibull Distribution with Different Numerical Estimation Methods: A Case Study

Alanazi,

Aloraini,

Islam

et al. 2023

Emerg Sci J

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The demand for electrical energy is increasing every day, which is one of the critical challenges facing the world today. Hence, the necessity of turning to clean renewable energy sources that are not harmful to the environment as an alternative to the traditional generation based on fossil fuels has become more important than ever before. Wind power is one of the renewable sources that provides a clean solution to generate electricity. In this context, the Kingdom of Saudi Arabia announces renewable energy projects to generate 9 GW from wind in 2032. Hence, the aim of this paper is to investigate the most suitable method of Weibull parameter estimation in order to predict wind characteristics and employ it for wind energy assessment in the Qassim region located in the center of the country. In this study, wind data is collected from NASA's forecasts of global energy resources for 2010–2015 based on their availability at altitudes of 10m and 50m and analyzed by using six different methods for Weibull parameter estimation: the graphical method (GM), standard deviation method (SDM), energy pattern factor method (EPF), moment method (MM), alternative maximum likelihood method (AMLM), and novel energy pattern factor method (NEPF). The efficiency of each method is tested by calculating the root mean square error (RMSE) and the relative wind power density error (RPDE). The comparison shows that the most appropriate method for estimating wind power density in the country is the Moment Method (MM), with the lowest RPDE ratio equal to 0.2018%. It has been found that the wind power density in the Qassim region falls into the class 1 category, as it is less than 100 W/m2 at a height of 10m and less than 200 W/m2at an altitude of 50m. The results show the region is only suitable for small off-grid projects. Doi: 10.28991/ESJ-2023-07-06-024 Full Text: PDF

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Determination of Weibull parameters with using Standard Deviation Method and performance comparison at different locations

Cited by 3 publications

References 24 publications

The investigation of the compliance of offshore wind data with the Weibull distribution function with using six different methods

The investigation of the compliance of offshore wind data with the Weibull distribution function with using six different methods

Statistical characteristics, probability distribution, and power potential of sea water velocity in Turkey

Wind Energy Assessment Using Weibull Distribution with Different Numerical Estimation Methods: A Case Study

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