Investigation of Wind Energy Resource on the Basis of Weibull and Rayleigh Models in North Eastern and Western, Nigeria

Abdullahi Ahmed; Bashir Isyaku Kunya

doi:doi:10.11648/j.ajae.20190601.15

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Investigation of Wind Energy Resource on the Basis of Weibull and Rayleigh Models in North Eastern and Western, Nigeria

Abdullahi Ahmed, Bashir Isyaku Kunya

Published in American Journal of Aerospace Engineering (Volume 6, Issue 1)

Received: 31 July 2019 Accepted: 28 August 2019 Published: 16 September 2019

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Abstract

This study is aimed to investigate wind energy resource on the basis of Weibull and Rayleigh models in north eastern (Bauchi and Maiduguri) and western (Kano and Sokoto) Nigeria, seventeen years (2000-2016) monthly wind speed data were collected from Nigeria meteorological station, Abuja at 10m height. The probability distribution function (pdf) of wind speed is very important tool needed in wind energy resource investigation, since wind power is proportional to the cube of wind speed. The Weibull parameters shape (k) and scale (c) for the four locations were determined and the values obtained for shape factors in Bauchi and Maiduguri range from 6.91 to 7.21 and Sokoto and Kano range from 9.27 to 10.68, while scale factors is in the range of 3.46 to 7.24 and 9.32 to 11.24, respectively. The Weibull model was found to be better fit than the Rayleigh model in analyzing the wind speed data. The north western part of Nigeria was found to have higher wind power density as compared to the north eastern part of the country.

Published in	American Journal of Aerospace Engineering (Volume 6, Issue 1)
DOI	10.11648/j.ajae.20190601.15
Page(s)	27-32
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), 2024. Published by Science Publishing Group

Keywords

Wind Power Density, Weibull Distribution, Rayleigh Distribution, Wind Speed Distribution

References

[1]	Ahmed, S. A. S. and Hanitseh, R. (2006). Evaluation of wind energy potential and electricity generation on the coast of Mediterranean sea in Egypt. Renewable Energy, 31: 1183-1202.
[2]	Hossain, J., Shina, V. and Kishore V. V. N (2011). A GIS based assessment of potential wind farms in India. Renewable Energy, 36: 3257-67.
[3]	Diaf, S. and Notton, G. (2013). Evaluation of electricity generation and energy cost of wind energy conversion system in Southern Algeria. Renewable and Sustainable Energy Reviews, 23: 379-390.
[4]	Ahmed, A. (2016). An assessment of wind power density in south east Nigeria, Enugu. American Journal of Modern Energy. 6: 1-5.
[5]	Proma, A. K., Pobitra, K. H. and Sabbir, R. (2014). Wind energy potential estimation for different region of Bangladesh. International Journal of Renewable and Sustainable Energy, 3: 47-52.
[6]	Ucar, A. and Balo, F. (2008). Investigation of wind characteristics and assessment of wind generation potentiality in Uludag – Bursa, Turkey Applied Energy, 86: 333-339.
[7]	Schmid, J and Palz, W. (1896). European wind energy technology, state of the art of wind energy converts in the European community, series. Volume 3, published by D. Radel publishing company.
[8]	Alsaad, M. A. (2013). Wind energy potential in selected areas in Jordan. Energy Conversion and Management, 65: 704-708.
[9]	Ojosu, J. O. and Salawu, R. I. (1989). A statistical analysis of wind energy potential for power generation in Nigeria. Nigeria Journal of Solar Energy, 8: 273-288.
[10]	Zeljko. D. And Jovan. M. (2012). Assessment of wind energy resource in the south Banat region of Serbia. Renewable and Sustainable Energy, 16: 3014-3023.
[11]	Akpinar, E. K. and Akpinar, S. (2004). Statistical analysis of wind energy potential on the basis of the Weibull and Rayleigh distributions for Agin-Elazig, Turkey. Power and Energy. 218: 557-565.
[12]	Celik, A. N. (2003). Assessing the suitability of wind speed probability distribution functions based on the wind power density. Renewable Energy, 28: 1563-1574.
[13]	Chen, K., Song, M. X. and Zhang, X. (2013). A statistical method to merge wind cases for wind power assessment of wind farm. Journal of Wind Engineering and Industrial Aerodynamics, 119: 69-77.
[14]	Mostafaeipour, A., Sedaghat, A., Dehgann-Niri, A. A., and Kalantar, V. (2011). Wind energy feasibility study for city of Sharbabak in Iran. Renewable and Sustainable Energy Review, 15: 2545-2456.
[15]	Feregh, G. M., Darwish A. S. K. and Sayigh, A. A. M. (1990). Wind energy potential for Bharain. Proceedings of the first World Renewable Energy Congress, United Kingdom, 2: 156-159.
[16]	Ahmed, A. (2018). Estimation of wind energy potential for two locations in north-east region of Nigeria. International Journal of Advance Trends in Engineering, Science and Technology, 5: 6-10.

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APA Style

Abdullahi Ahmed, Bashir Isyaku Kunya. (2019). Investigation of Wind Energy Resource on the Basis of Weibull and Rayleigh Models in North Eastern and Western, Nigeria. American Journal of Aerospace Engineering, 6(1), 27-32. https://doi.org/10.11648/j.ajae.20190601.15

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ACS Style

Abdullahi Ahmed; Bashir Isyaku Kunya. Investigation of Wind Energy Resource on the Basis of Weibull and Rayleigh Models in North Eastern and Western, Nigeria. Am. J. Aerosp. Eng. 2019, 6(1), 27-32. doi: 10.11648/j.ajae.20190601.15

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AMA Style

Abdullahi Ahmed, Bashir Isyaku Kunya. Investigation of Wind Energy Resource on the Basis of Weibull and Rayleigh Models in North Eastern and Western, Nigeria. Am J Aerosp Eng. 2019;6(1):27-32. doi: 10.11648/j.ajae.20190601.15

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@article{10.11648/j.ajae.20190601.15,
  author = {Abdullahi Ahmed and Bashir Isyaku Kunya},
  title = {Investigation of Wind Energy Resource on the Basis of Weibull and Rayleigh Models in North Eastern and Western, Nigeria},
  journal = {American Journal of Aerospace Engineering},
  volume = {6},
  number = {1},
  pages = {27-32},
  doi = {10.11648/j.ajae.20190601.15},
  url = {https://doi.org/10.11648/j.ajae.20190601.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajae.20190601.15},
  abstract = {This study is aimed to investigate wind energy resource on the basis of Weibull and Rayleigh models in north eastern (Bauchi and Maiduguri) and western (Kano and Sokoto) Nigeria, seventeen years (2000-2016) monthly wind speed data were collected from Nigeria meteorological station, Abuja at 10m height. The probability distribution function (pdf) of wind speed is very important tool needed in wind energy resource investigation, since wind power is proportional to the cube of wind speed. The Weibull parameters shape (k) and scale (c) for the four locations were determined and the values obtained for shape factors in Bauchi and Maiduguri range from 6.91 to 7.21 and Sokoto and Kano range from 9.27 to 10.68, while scale factors is in the range of 3.46 to 7.24 and 9.32 to 11.24, respectively. The Weibull model was found to be better fit than the Rayleigh model in analyzing the wind speed data. The north western part of Nigeria was found to have higher wind power density as compared to the north eastern part of the country.},
 year = {2019}
}

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TY  - JOUR
T1  - Investigation of Wind Energy Resource on the Basis of Weibull and Rayleigh Models in North Eastern and Western, Nigeria
AU  - Abdullahi Ahmed
AU  - Bashir Isyaku Kunya
Y1  - 2019/09/16
PY  - 2019
N1  - https://doi.org/10.11648/j.ajae.20190601.15
DO  - 10.11648/j.ajae.20190601.15
T2  - American Journal of Aerospace Engineering
JF  - American Journal of Aerospace Engineering
JO  - American Journal of Aerospace Engineering
SP  - 27
EP  - 32
PB  - Science Publishing Group
SN  - 2376-4821
UR  - https://doi.org/10.11648/j.ajae.20190601.15
AB  - This study is aimed to investigate wind energy resource on the basis of Weibull and Rayleigh models in north eastern (Bauchi and Maiduguri) and western (Kano and Sokoto) Nigeria, seventeen years (2000-2016) monthly wind speed data were collected from Nigeria meteorological station, Abuja at 10m height. The probability distribution function (pdf) of wind speed is very important tool needed in wind energy resource investigation, since wind power is proportional to the cube of wind speed. The Weibull parameters shape (k) and scale (c) for the four locations were determined and the values obtained for shape factors in Bauchi and Maiduguri range from 6.91 to 7.21 and Sokoto and Kano range from 9.27 to 10.68, while scale factors is in the range of 3.46 to 7.24 and 9.32 to 11.24, respectively. The Weibull model was found to be better fit than the Rayleigh model in analyzing the wind speed data. The north western part of Nigeria was found to have higher wind power density as compared to the north eastern part of the country.
VL  - 6
IS  - 1
ER  -

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Author Information

Abdullahi Ahmed

Department of Mechanical Engineering, Kano University of Science and Technology, Wudil, Nigeria
Bashir Isyaku Kunya

Department of Mechanical Engineering, Kano University of Science and Technology, Wudil, Nigeria

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APA Style

Abdullahi Ahmed, Bashir Isyaku Kunya. (2019). Investigation of Wind Energy Resource on the Basis of Weibull and Rayleigh Models in North Eastern and Western, Nigeria. American Journal of Aerospace Engineering, 6(1), 27-32. https://doi.org/10.11648/j.ajae.20190601.15

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ACS Style

Abdullahi Ahmed; Bashir Isyaku Kunya. Investigation of Wind Energy Resource on the Basis of Weibull and Rayleigh Models in North Eastern and Western, Nigeria. Am. J. Aerosp. Eng. 2019, 6(1), 27-32. doi: 10.11648/j.ajae.20190601.15

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AMA Style

Abdullahi Ahmed, Bashir Isyaku Kunya. Investigation of Wind Energy Resource on the Basis of Weibull and Rayleigh Models in North Eastern and Western, Nigeria. Am J Aerosp Eng. 2019;6(1):27-32. doi: 10.11648/j.ajae.20190601.15

Copy | Download

@article{10.11648/j.ajae.20190601.15,
  author = {Abdullahi Ahmed and Bashir Isyaku Kunya},
  title = {Investigation of Wind Energy Resource on the Basis of Weibull and Rayleigh Models in North Eastern and Western, Nigeria},
  journal = {American Journal of Aerospace Engineering},
  volume = {6},
  number = {1},
  pages = {27-32},
  doi = {10.11648/j.ajae.20190601.15},
  url = {https://doi.org/10.11648/j.ajae.20190601.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajae.20190601.15},
  abstract = {This study is aimed to investigate wind energy resource on the basis of Weibull and Rayleigh models in north eastern (Bauchi and Maiduguri) and western (Kano and Sokoto) Nigeria, seventeen years (2000-2016) monthly wind speed data were collected from Nigeria meteorological station, Abuja at 10m height. The probability distribution function (pdf) of wind speed is very important tool needed in wind energy resource investigation, since wind power is proportional to the cube of wind speed. The Weibull parameters shape (k) and scale (c) for the four locations were determined and the values obtained for shape factors in Bauchi and Maiduguri range from 6.91 to 7.21 and Sokoto and Kano range from 9.27 to 10.68, while scale factors is in the range of 3.46 to 7.24 and 9.32 to 11.24, respectively. The Weibull model was found to be better fit than the Rayleigh model in analyzing the wind speed data. The north western part of Nigeria was found to have higher wind power density as compared to the north eastern part of the country.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - Investigation of Wind Energy Resource on the Basis of Weibull and Rayleigh Models in North Eastern and Western, Nigeria
AU  - Abdullahi Ahmed
AU  - Bashir Isyaku Kunya
Y1  - 2019/09/16
PY  - 2019
N1  - https://doi.org/10.11648/j.ajae.20190601.15
DO  - 10.11648/j.ajae.20190601.15
T2  - American Journal of Aerospace Engineering
JF  - American Journal of Aerospace Engineering
JO  - American Journal of Aerospace Engineering
SP  - 27
EP  - 32
PB  - Science Publishing Group
SN  - 2376-4821
UR  - https://doi.org/10.11648/j.ajae.20190601.15
AB  - This study is aimed to investigate wind energy resource on the basis of Weibull and Rayleigh models in north eastern (Bauchi and Maiduguri) and western (Kano and Sokoto) Nigeria, seventeen years (2000-2016) monthly wind speed data were collected from Nigeria meteorological station, Abuja at 10m height. The probability distribution function (pdf) of wind speed is very important tool needed in wind energy resource investigation, since wind power is proportional to the cube of wind speed. The Weibull parameters shape (k) and scale (c) for the four locations were determined and the values obtained for shape factors in Bauchi and Maiduguri range from 6.91 to 7.21 and Sokoto and Kano range from 9.27 to 10.68, while scale factors is in the range of 3.46 to 7.24 and 9.32 to 11.24, respectively. The Weibull model was found to be better fit than the Rayleigh model in analyzing the wind speed data. The north western part of Nigeria was found to have higher wind power density as compared to the north eastern part of the country.
VL  - 6
IS  - 1
ER  -

Copy | Download