Analysis of Wind Speed Distribution: Comparative Study of Weibull to Rayleigh Probability Density Function; A Case of Two Sites in Ethiopia

Girma Dejene Nage

doi:doi:10.11648/j.ajme.20160203.11

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Analysis of Wind Speed Distribution: Comparative Study of Weibull to Rayleigh Probability Density Function; A Case of Two Sites in Ethiopia

Girma Dejene Nage

Published in American Journal of Modern Energy (Volume 2, Issue 3)

Received: 30 June 2016 Accepted: 28 July 2016 Published: 26 August 2016

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Abstract

This study is primarily aimed to estimate the wind speed distribution of the location, Dire Dawa and Hawasa. Wind speed is the most important parameter in the analysis of wind energy resource, design and study of wind energy conversion systems. In this study, statistical methods were used to analyze wind speed data of Dire Dawa and Hawasa. Based on these data, the shape, k and scale, c parameters of the two locations were determined. The monthly mean values of k range from 1.86 to 8.19, with yearly mean value of 4.46, while c is in the range of 1.60 to 3.65 m/s with yearly mean value of 2.59 m/s for Dire Dawa and monthly mean values of k range from 2.00 to 2.79, with yearly mean value of 2.38, while c is in the range of 1.50 to 2.19 m/s with yearly mean value of 1.76 m/s for Hawasa. Two probability density functions are fitted to the measured probability distributions on a monthly basis. From statistical analysis of distributions, the Weibull distribution is better in fitting the measured probability density distributions than the Rayleigh distribution for the whole year. The cumulative probability distribution indicates, the probability for which the wind blows with a monthly mean wind speed v is equal or lower than 5 m/s is almost one.

Published in	American Journal of Modern Energy (Volume 2, Issue 3)
DOI	10.11648/j.ajme.20160203.11
Page(s)	10-16
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

Weibull Distribution, Rayleigh Distribution, Wind Speed Distribution, Weibull Parameters

References

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Girma Dejene Nage. (2016). Analysis of Wind Speed Distribution: Comparative Study of Weibull to Rayleigh Probability Density Function; A Case of Two Sites in Ethiopia. American Journal of Modern Energy, 2(3), 10-16. https://doi.org/10.11648/j.ajme.20160203.11

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ACS Style

Girma Dejene Nage. Analysis of Wind Speed Distribution: Comparative Study of Weibull to Rayleigh Probability Density Function; A Case of Two Sites in Ethiopia. Am. J. Mod. Energy 2016, 2(3), 10-16. doi: 10.11648/j.ajme.20160203.11

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AMA Style

Girma Dejene Nage. Analysis of Wind Speed Distribution: Comparative Study of Weibull to Rayleigh Probability Density Function; A Case of Two Sites in Ethiopia. Am J Mod Energy. 2016;2(3):10-16. doi: 10.11648/j.ajme.20160203.11

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@article{10.11648/j.ajme.20160203.11,
  author = {Girma Dejene Nage},
  title = {Analysis of Wind Speed Distribution: Comparative Study of Weibull to Rayleigh Probability Density Function; A Case of Two Sites in Ethiopia},
  journal = {American Journal of Modern Energy},
  volume = {2},
  number = {3},
  pages = {10-16},
  doi = {10.11648/j.ajme.20160203.11},
  url = {https://doi.org/10.11648/j.ajme.20160203.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajme.20160203.11},
  abstract = {This study is primarily aimed to estimate the wind speed distribution of the location, Dire Dawa and Hawasa. Wind speed is the most important parameter in the analysis of wind energy resource, design and study of wind energy conversion systems. In this study, statistical methods were used to analyze wind speed data of Dire Dawa and Hawasa. Based on these data, the shape, k and scale, c parameters of the two locations were determined. The monthly mean values of k range from 1.86 to 8.19, with yearly mean value of 4.46, while c is in the range of 1.60 to 3.65 m/s with yearly mean value of 2.59 m/s for Dire Dawa and monthly mean values of k range from 2.00 to 2.79, with yearly mean value of 2.38, while c is in the range of 1.50 to 2.19 m/s with yearly mean value of 1.76 m/s for Hawasa. Two probability density functions are fitted to the measured probability distributions on a monthly basis. From statistical analysis of distributions, the Weibull distribution is better in fitting the measured probability density distributions than the Rayleigh distribution for the whole year. The cumulative probability distribution indicates, the probability for which the wind blows with a monthly mean wind speed v is equal or lower than 5 m/s is almost one.},
 year = {2016}
}

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TY  - JOUR
T1  - Analysis of Wind Speed Distribution: Comparative Study of Weibull to Rayleigh Probability Density Function; A Case of Two Sites in Ethiopia
AU  - Girma Dejene Nage
Y1  - 2016/08/26
PY  - 2016
N1  - https://doi.org/10.11648/j.ajme.20160203.11
DO  - 10.11648/j.ajme.20160203.11
T2  - American Journal of Modern Energy
JF  - American Journal of Modern Energy
JO  - American Journal of Modern Energy
SP  - 10
EP  - 16
PB  - Science Publishing Group
SN  - 2575-3797
UR  - https://doi.org/10.11648/j.ajme.20160203.11
AB  - This study is primarily aimed to estimate the wind speed distribution of the location, Dire Dawa and Hawasa. Wind speed is the most important parameter in the analysis of wind energy resource, design and study of wind energy conversion systems. In this study, statistical methods were used to analyze wind speed data of Dire Dawa and Hawasa. Based on these data, the shape, k and scale, c parameters of the two locations were determined. The monthly mean values of k range from 1.86 to 8.19, with yearly mean value of 4.46, while c is in the range of 1.60 to 3.65 m/s with yearly mean value of 2.59 m/s for Dire Dawa and monthly mean values of k range from 2.00 to 2.79, with yearly mean value of 2.38, while c is in the range of 1.50 to 2.19 m/s with yearly mean value of 1.76 m/s for Hawasa. Two probability density functions are fitted to the measured probability distributions on a monthly basis. From statistical analysis of distributions, the Weibull distribution is better in fitting the measured probability density distributions than the Rayleigh distribution for the whole year. The cumulative probability distribution indicates, the probability for which the wind blows with a monthly mean wind speed v is equal or lower than 5 m/s is almost one.
VL  - 2
IS  - 3
ER  -

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Author Information

Girma Dejene Nage

Department of Physics, College of Natural and Computational Sciences, Mizan-Tepi University, Tepi, Ethiopia

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Girma Dejene Nage. (2016). Analysis of Wind Speed Distribution: Comparative Study of Weibull to Rayleigh Probability Density Function; A Case of Two Sites in Ethiopia. American Journal of Modern Energy, 2(3), 10-16. https://doi.org/10.11648/j.ajme.20160203.11

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ACS Style

Girma Dejene Nage. Analysis of Wind Speed Distribution: Comparative Study of Weibull to Rayleigh Probability Density Function; A Case of Two Sites in Ethiopia. Am. J. Mod. Energy 2016, 2(3), 10-16. doi: 10.11648/j.ajme.20160203.11

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AMA Style

Girma Dejene Nage. Analysis of Wind Speed Distribution: Comparative Study of Weibull to Rayleigh Probability Density Function; A Case of Two Sites in Ethiopia. Am J Mod Energy. 2016;2(3):10-16. doi: 10.11648/j.ajme.20160203.11

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@article{10.11648/j.ajme.20160203.11,
  author = {Girma Dejene Nage},
  title = {Analysis of Wind Speed Distribution: Comparative Study of Weibull to Rayleigh Probability Density Function; A Case of Two Sites in Ethiopia},
  journal = {American Journal of Modern Energy},
  volume = {2},
  number = {3},
  pages = {10-16},
  doi = {10.11648/j.ajme.20160203.11},
  url = {https://doi.org/10.11648/j.ajme.20160203.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajme.20160203.11},
  abstract = {This study is primarily aimed to estimate the wind speed distribution of the location, Dire Dawa and Hawasa. Wind speed is the most important parameter in the analysis of wind energy resource, design and study of wind energy conversion systems. In this study, statistical methods were used to analyze wind speed data of Dire Dawa and Hawasa. Based on these data, the shape, k and scale, c parameters of the two locations were determined. The monthly mean values of k range from 1.86 to 8.19, with yearly mean value of 4.46, while c is in the range of 1.60 to 3.65 m/s with yearly mean value of 2.59 m/s for Dire Dawa and monthly mean values of k range from 2.00 to 2.79, with yearly mean value of 2.38, while c is in the range of 1.50 to 2.19 m/s with yearly mean value of 1.76 m/s for Hawasa. Two probability density functions are fitted to the measured probability distributions on a monthly basis. From statistical analysis of distributions, the Weibull distribution is better in fitting the measured probability density distributions than the Rayleigh distribution for the whole year. The cumulative probability distribution indicates, the probability for which the wind blows with a monthly mean wind speed v is equal or lower than 5 m/s is almost one.},
 year = {2016}
}

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TY  - JOUR
T1  - Analysis of Wind Speed Distribution: Comparative Study of Weibull to Rayleigh Probability Density Function; A Case of Two Sites in Ethiopia
AU  - Girma Dejene Nage
Y1  - 2016/08/26
PY  - 2016
N1  - https://doi.org/10.11648/j.ajme.20160203.11
DO  - 10.11648/j.ajme.20160203.11
T2  - American Journal of Modern Energy
JF  - American Journal of Modern Energy
JO  - American Journal of Modern Energy
SP  - 10
EP  - 16
PB  - Science Publishing Group
SN  - 2575-3797
UR  - https://doi.org/10.11648/j.ajme.20160203.11
AB  - This study is primarily aimed to estimate the wind speed distribution of the location, Dire Dawa and Hawasa. Wind speed is the most important parameter in the analysis of wind energy resource, design and study of wind energy conversion systems. In this study, statistical methods were used to analyze wind speed data of Dire Dawa and Hawasa. Based on these data, the shape, k and scale, c parameters of the two locations were determined. The monthly mean values of k range from 1.86 to 8.19, with yearly mean value of 4.46, while c is in the range of 1.60 to 3.65 m/s with yearly mean value of 2.59 m/s for Dire Dawa and monthly mean values of k range from 2.00 to 2.79, with yearly mean value of 2.38, while c is in the range of 1.50 to 2.19 m/s with yearly mean value of 1.76 m/s for Hawasa. Two probability density functions are fitted to the measured probability distributions on a monthly basis. From statistical analysis of distributions, the Weibull distribution is better in fitting the measured probability density distributions than the Rayleigh distribution for the whole year. The cumulative probability distribution indicates, the probability for which the wind blows with a monthly mean wind speed v is equal or lower than 5 m/s is almost one.
VL  - 2
IS  - 3
ER  -

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