On the development of new cosine-based probabilistic methods with applications to univariate and bivariate analyses of the wind speed energy
So far in the literature, a number of probability distributions have been successfully implemented for analyzing the wind speed and energy data sets. However, there is no published work on modeling and analyzing the wind speed and energy data sets with probability distributions that are introduced u...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-11-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023086905 |
| _version_ | 1827616034242166784 |
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| author | Badr Alnssyan Mohammed Ahmed Alomair |
| author_facet | Badr Alnssyan Mohammed Ahmed Alomair |
| author_sort | Badr Alnssyan |
| collection | DOAJ |
| description | So far in the literature, a number of probability distributions have been successfully implemented for analyzing the wind speed and energy data sets. However, there is no published work on modeling and analyzing the wind speed and energy data sets with probability distributions that are introduced using trigonometric functions. In the existing literature, there is also a lack of studies on implementing the bivariate trigonometric-based probability distributions for modeling the wind speed and energy data sets. In this paper, we take up a meaningful effort to cover these interesting research gaps. Thus, we first incorporate a cosine function and introduce a new univariate probability distributional method, namely, a univariate modified cosine-G (UMC-G) family. Using the UMC-G method, a new probability distribution called a univariate modified cosine-Weibull (UMC-Weibull) distribution is studied. We apply the UMC-Weibull distribution for analyzing the wind energy data set taken from the weather station at Sotavento Galicia, Spain. Furthermore, we also introduce a bivariate version of the UMC-G method using the Farlie–Gumble–Morgenstern copula approach. The proposed bivariate distributional method is called a bivariate modified cosine-G (BMC-G) family. A special member of the BMC-G distributions called a bivariate modified cosine-Weibull (BMC-Weibull) distribution is introduced. We apply the BMC-Weibull distribution for analyzing the bivariate data set representing the wind speed and energy taken from the weather station at Sotavento Galicia. Using different statistical tools, we observe that the UMC-Weibull and BMC-Weibull are the best-suited models for analyzing the wind speed and energy data sets. |
| first_indexed | 2024-03-09T09:20:03Z |
| format | Article |
| id | doaj.art-bd5179ef54834ea2896f949f15ebbde9 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-03-09T09:20:03Z |
| publishDate | 2023-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-bd5179ef54834ea2896f949f15ebbde92023-12-02T07:02:30ZengElsevierHeliyon2405-84402023-11-01911e21482On the development of new cosine-based probabilistic methods with applications to univariate and bivariate analyses of the wind speed energyBadr Alnssyan0Mohammed Ahmed Alomair1Unit of Scientific Research, Applied College, Qassim University, Buraydah 51452, Saudi ArabiaDepartment of Quantitative Methods, School of Business, King Faisal University, Al-Ahsa 31982, Saudi Arabia; Corresponding author.So far in the literature, a number of probability distributions have been successfully implemented for analyzing the wind speed and energy data sets. However, there is no published work on modeling and analyzing the wind speed and energy data sets with probability distributions that are introduced using trigonometric functions. In the existing literature, there is also a lack of studies on implementing the bivariate trigonometric-based probability distributions for modeling the wind speed and energy data sets. In this paper, we take up a meaningful effort to cover these interesting research gaps. Thus, we first incorporate a cosine function and introduce a new univariate probability distributional method, namely, a univariate modified cosine-G (UMC-G) family. Using the UMC-G method, a new probability distribution called a univariate modified cosine-Weibull (UMC-Weibull) distribution is studied. We apply the UMC-Weibull distribution for analyzing the wind energy data set taken from the weather station at Sotavento Galicia, Spain. Furthermore, we also introduce a bivariate version of the UMC-G method using the Farlie–Gumble–Morgenstern copula approach. The proposed bivariate distributional method is called a bivariate modified cosine-G (BMC-G) family. A special member of the BMC-G distributions called a bivariate modified cosine-Weibull (BMC-Weibull) distribution is introduced. We apply the BMC-Weibull distribution for analyzing the bivariate data set representing the wind speed and energy taken from the weather station at Sotavento Galicia. Using different statistical tools, we observe that the UMC-Weibull and BMC-Weibull are the best-suited models for analyzing the wind speed and energy data sets.http://www.sciencedirect.com/science/article/pii/S2405844023086905Weibull distributionCosine functionUnivariate and bivariate distributionsWind speedEnergyStatistical modeling |
| spellingShingle | Badr Alnssyan Mohammed Ahmed Alomair On the development of new cosine-based probabilistic methods with applications to univariate and bivariate analyses of the wind speed energy Heliyon Weibull distribution Cosine function Univariate and bivariate distributions Wind speed Energy Statistical modeling |
| title | On the development of new cosine-based probabilistic methods with applications to univariate and bivariate analyses of the wind speed energy |
| title_full | On the development of new cosine-based probabilistic methods with applications to univariate and bivariate analyses of the wind speed energy |
| title_fullStr | On the development of new cosine-based probabilistic methods with applications to univariate and bivariate analyses of the wind speed energy |
| title_full_unstemmed | On the development of new cosine-based probabilistic methods with applications to univariate and bivariate analyses of the wind speed energy |
| title_short | On the development of new cosine-based probabilistic methods with applications to univariate and bivariate analyses of the wind speed energy |
| title_sort | on the development of new cosine based probabilistic methods with applications to univariate and bivariate analyses of the wind speed energy |
| topic | Weibull distribution Cosine function Univariate and bivariate distributions Wind speed Energy Statistical modeling |
| url | http://www.sciencedirect.com/science/article/pii/S2405844023086905 |
| work_keys_str_mv | AT badralnssyan onthedevelopmentofnewcosinebasedprobabilisticmethodswithapplicationstounivariateandbivariateanalysesofthewindspeedenergy AT mohammedahmedalomair onthedevelopmentofnewcosinebasedprobabilisticmethodswithapplicationstounivariateandbivariateanalysesofthewindspeedenergy |