Statistical analysis of wind speed for electrical power generation in some selected sites in northern Nigeria

Abdulkarim, Abubakar; Abdelkader, Sobhy M.; Morrow, D.J.; Falade, A. J.; Adediran, YA

doi:10.4314/njt.v36i4.35

Cited by 13 publications

(11 citation statements)

References 16 publications

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“…The parameters of the Weibull distribution function consist of the scale parameter and shape parameter. The Weibull PDF, CDF, and QF are given below in (2) to (4), respectively [3,13,14]. In (3), when the scale parameter and the wind speed are equal, ( ) becomes about 0.632.…”

Section: ) Overview Of Parametric Distribution Functionsmentioning

confidence: 99%

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Modeling Wind Speed Using Parametric and Non-Parametric Distribution Functions

Ncwane

Folly

2021

IEEE Access

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The variability of wind speed is modeled in the literature using probability distribution functions (PDFs). In many papers, the selection of PDFs is based solely on goodness of fit metrics without giving proper consideration as to whether these PDFs can model the wind speed range. A PDF's ability to model the wind speed range ensures that it can synthesize both the minimum and maximum wind speed at a site. A methodology to select PDFs that can be used to model wind speed is presented in this paper. The proposed methodology not only considers goodness of fit metrics when selecting PDFs but also their ability to model the wind speed range. The proposed methodology is compared with a commonly used methodology in the literature where the PDFs are selected based solely on goodness of fit metrics. Simulation results show that the proposed methodology chooses better PDFs than the commonly used methodology in the literature. Furthermore, it is shown that selecting PDFs using the commonly used methodology in the literature does not guarantee that the chosen PDFs will model the wind speed range.

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Section: ) Overview Of Parametric Distribution Functionsmentioning

confidence: 99%

“…The Wakeby distribution function parameters consist of the location parameter, first and second scale parameters, and the first and second shape parameters. The Wakeby PDF is given in (11) [5,10,14], while the Wakeby CDF given in (12) is the inverse of the Wakeby QF given in (13) [5,6,14].…”

Section: ) Overview Of Parametric Distribution Functionsmentioning

confidence: 99%

Modeling Wind Speed Using Parametric and Non-Parametric Distribution Functions

Ncwane

Folly

2021

IEEE Access

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“…Once a distribution does not observe the normality test, [23] suggested that the option inferential statistic was to use multivariate GARCH with its error distribution assumptions with fixed degree of freedom.…”

Section: Descriptive Test Statistic For Normality Testmentioning

confidence: 99%

Multivariate Garch Analysis of Selected Nigerian Economic Data

Pepple¹,

Harrison

Essi

2021

AJPAS

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Aims: The aim of this study is to examine multivariate GARCH modeling of selected Nigerian economic data. Study Design: The study used monthly data of Nigerian crude oil prices (dollar Per Barrel), consumer price Index rural, maximum lending rate and prime lending rate. Methodology: This work covers time series data on crude oil prices, consumer price Index rural, maximum lending rate and prime lending rate extracted from Central Bank of Nigeria (CBN) from 2000 to 2019. In attempt to achieve the aim of the study, quadrivariate VECH and DCC model were applied. Results: The results confirmed that returns on economic data were correlated. Also, diagonal multivariate VECH model confirmed one of the properties that it must be ‘positive semi-definite’, And the DCC confirmed also the positive-definite conditional-variance. Conclusion: From the results obtained, it was confirmed that there exists a strong confirmation of a time-varying conditional covariance and interdependence among Nigeria economic data. As for cross-volatility effects, past innovations in crude oil price have utmost control on future volatility of returns on economic data. It was also confirmed that time varying covariance displays among these economic data and lower degree of persistence and based on Model selection criteria using the Akaike information criteria (AIC) has 17.485 for diagonal VECH while for DCC has 17.509 AIC which makes VECH model better fitted.

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“…Statistical studies have shown that the twoparameter gamma distribution is adequate to describe the distribution of surface wind speeds almost everywhere in Europe [28]. The probability density function and the cumulative function of the 2-parameter generalized Gamma distribution are given by equations ( 13) and ( 14), respectively.…”

Section: The Two-parameter Gamma Distribution Functionmentioning

confidence: 99%

Assessing the Best Fit Probability Distribution Model for Wind Speed Data for Different Sites of Burkina Faso

Boro¹,

Thierry²,

Kieno³

et al. 2020

CJAST

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In order to estimate the power output of a wind turbine, optimise its sizing and forecast the economic rate of return and risks of a wind energy project, wind speed distribution modelling is crucial. For which, Weibull distribution is considered as one of the most acceptable model. However, this distribution does not fit certain wind speed regimes. The objective of this study is to model the frequency distribution of the three-hourly wind speed at ten sites of Burkina Faso. In this context, we compared the accuracy of five distributions (Weibull, Hybrid Weibull, Rayleigh, Gamma and inverse Gaussian) which gave satisfactory results in this field. The maximum likelihood method was used to fit the distributions to the measured data. According to the statistical analysis tools (the coefficient of determination and the root mean square error), it was found that the Weibull distribution is most suited to the Bobo, Dédougou, Ouaga and Ouahigouya sites. On the other hand, for the sites of Bogandé, Fada and Po, the hybrid Weibull distribution is the most suitable one. As to the inverse Gaussian distribution, it is the most suitable for the Boromo, Dori and Gaoua sites. In addition, the analysis focused on comparing the mean absolute error of the annual wind power density estimation using the distributions examined. The Hybrid Weibull distribution was found to have a minimal mean absolute error for most study sites.

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Statistical analysis of wind speed for electrical power generation in some selected sites in northern Nigeria

Cited by 13 publications

References 16 publications

Modeling Wind Speed Using Parametric and Non-Parametric Distribution Functions

Modeling Wind Speed Using Parametric and Non-Parametric Distribution Functions

Multivariate Garch Analysis of Selected Nigerian Economic Data

Assessing the Best Fit Probability Distribution Model for Wind Speed Data for Different Sites of Burkina Faso

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