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Technical analysis of wind energy potentials using a modified Weibull and Raleigh distribution model parameters approach in the Gambia

Wind energy has gained prominence over the past few decades because of its environment-friendly nature and abundant availability. However, the exploration of wind energy requires adequate knowledge of the wind distribution parameters before installing the wind turbine. This study assessed the potent...

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Autores principales: Ayua, Tyoyima John, Emetere, Moses Eterigho
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10560052/
https://www.ncbi.nlm.nih.gov/pubmed/37809563
http://dx.doi.org/10.1016/j.heliyon.2023.e20315
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author Ayua, Tyoyima John
Emetere, Moses Eterigho
author_facet Ayua, Tyoyima John
Emetere, Moses Eterigho
author_sort Ayua, Tyoyima John
collection PubMed
description Wind energy has gained prominence over the past few decades because of its environment-friendly nature and abundant availability. However, the exploration of wind energy requires adequate knowledge of the wind distribution parameters before installing the wind turbine. This study assessed the potential of harvesting wind energy at two Gambian locations by fitting the best model comparing Weibull and Raleigh Distributions. A novel approach combining the energy pattern factor and standard deviation methods in estimating the distribution parameters of the characteristics of wind in the Gambian locations of Yundum and Basse has been presented and statistically analyzed using the Weibull and Raleigh distribution functions. The results showed that the shape parameters ranged from 4.88 to 6.98 and 3.87–6.15 for Yundum and Basse locations, the Weibull scale parameter ranged from 6.60 to 10.58 m/s and 4.51–8.69 m/s for Yundum and Basse while the calculated wind power densities ranged from 139 to 718 W/m(2) and 46–390 W/m(2) for Yundum and Basse respectively. These results clearly show a high potential for generating electricity with wind in the study areas. The statistical analysis revealed that the Weibull models perform better at Yundum in terms of [Formula: see text]  = 0.33, [Formula: see text] and [Formula: see text] 1.57 while the Raleigh distribution gives a better fit for Basse in terms of [Formula: see text] and [Formula: see text] only making it more suitable for calculating the wind power potentials.
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spelling pubmed-105600522023-10-08 Technical analysis of wind energy potentials using a modified Weibull and Raleigh distribution model parameters approach in the Gambia Ayua, Tyoyima John Emetere, Moses Eterigho Heliyon Research Article Wind energy has gained prominence over the past few decades because of its environment-friendly nature and abundant availability. However, the exploration of wind energy requires adequate knowledge of the wind distribution parameters before installing the wind turbine. This study assessed the potential of harvesting wind energy at two Gambian locations by fitting the best model comparing Weibull and Raleigh Distributions. A novel approach combining the energy pattern factor and standard deviation methods in estimating the distribution parameters of the characteristics of wind in the Gambian locations of Yundum and Basse has been presented and statistically analyzed using the Weibull and Raleigh distribution functions. The results showed that the shape parameters ranged from 4.88 to 6.98 and 3.87–6.15 for Yundum and Basse locations, the Weibull scale parameter ranged from 6.60 to 10.58 m/s and 4.51–8.69 m/s for Yundum and Basse while the calculated wind power densities ranged from 139 to 718 W/m(2) and 46–390 W/m(2) for Yundum and Basse respectively. These results clearly show a high potential for generating electricity with wind in the study areas. The statistical analysis revealed that the Weibull models perform better at Yundum in terms of [Formula: see text]  = 0.33, [Formula: see text] and [Formula: see text] 1.57 while the Raleigh distribution gives a better fit for Basse in terms of [Formula: see text] and [Formula: see text] only making it more suitable for calculating the wind power potentials. Elsevier 2023-09-19 /pmc/articles/PMC10560052/ /pubmed/37809563 http://dx.doi.org/10.1016/j.heliyon.2023.e20315 Text en © 2023 Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Ayua, Tyoyima John
Emetere, Moses Eterigho
Technical analysis of wind energy potentials using a modified Weibull and Raleigh distribution model parameters approach in the Gambia
title Technical analysis of wind energy potentials using a modified Weibull and Raleigh distribution model parameters approach in the Gambia
title_full Technical analysis of wind energy potentials using a modified Weibull and Raleigh distribution model parameters approach in the Gambia
title_fullStr Technical analysis of wind energy potentials using a modified Weibull and Raleigh distribution model parameters approach in the Gambia
title_full_unstemmed Technical analysis of wind energy potentials using a modified Weibull and Raleigh distribution model parameters approach in the Gambia
title_short Technical analysis of wind energy potentials using a modified Weibull and Raleigh distribution model parameters approach in the Gambia
title_sort technical analysis of wind energy potentials using a modified weibull and raleigh distribution model parameters approach in the gambia
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10560052/
https://www.ncbi.nlm.nih.gov/pubmed/37809563
http://dx.doi.org/10.1016/j.heliyon.2023.e20315
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