Analysis of Wind Energy Potential in North East Nigeria

A. Ahmed; A. A. Bello; D. Habou

doi:doi:10.11648/j.jenr.20140304.11

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Analysis of Wind Energy Potential in North East Nigeria

A. Ahmed, A. A. Bello, D. Habou

Published in Journal of Energy and Natural Resources (Volume 3, Issue 4)

Received: 11 July 2014 Accepted: 28 July 2014 Published: 10 August 2014

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Abstract

This research reports wind energy potential evaluation of two locations in the north east Nigeria (Bauchi and Borno). The evaluation is based on Weibull and Rayleigh models using 17 years mean monthly wind speed data covering the period (1990-2006). The result shows that Rayleigh is best fit model that describes the wind speed data at 10 m height. Reference mean power density (based on the measured probability distribution) was compared with those obtained from the Weibull and Rayleigh models. In calculating the percentage error, results shows that Weibull provided better power density estimation in all 12 months than the Rayleigh model. From this research work, it was found that Borno has high wind power density 273.16 W/m2 for Weibull and 365.77 W/m2 for Rayleigh in the month of June as compared Bauchi with highest power density of 31.45 W/m2 for Weibull and 37.06 W/m2 for Rayleigh in the month of May.

Published in	Journal of Energy and Natural Resources (Volume 3, Issue 4)
DOI	10.11648/j.jenr.20140304.11
Page(s)	46-50
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 Energy Potential, Nigeria, Generation, Weibull, Rayleigh, Probability Density Function

References

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[2]	Ahmed Shata AS, Hanistsch R. The potential of electricity generation on the east coast of Red Sea in Egypt. Renewable Energy 2006; 31: 1597 – 625.
[3]	Ahmed SA. Investigation of wind characteristics and wind energy potential at RAS Ghareb, Egypt. Renewable and Sustainable Energy Reviews 2011; 15: 2750 – 5.
[4]	Akpinar EK, Akpinar S. Determination of the wind energy potential for Maden-Elazig, Turkey. Energy Conversion and Management 2004; 45: 2901-14.
[5]	Brano VL, Orioli A, Ciulla G, Culotta S. Quality of wind speed fitting distributions for the urban area of Palermo, Italy. Renewable Energy 2011; 36:1026 – 39.
[6]	Celik AN. On the distributional parameters used in assessment of the suitability of wind speed probability density functions. Energy Conversion and Management 2004; 45: 1735 – 47.
[7]	Celik AN. A statistical analysis of wind power density based on the Weibull and Rayleigh Models at the southern region of Turkey. Renewable Energy 2004; 29:593 – 604.
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[9]	Oztopal A, Sahin AD, Akgun N, Sen Z. On the regional wind energy potential of Turkey. Energy 2000; 25: 189 – 200.
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APA Style

A. Ahmed, A. A. Bello, D. Habou. (2014). Analysis of Wind Energy Potential in North East Nigeria. Journal of Energy and Natural Resources, 3(4), 46-50. https://doi.org/10.11648/j.jenr.20140304.11

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ACS Style

A. Ahmed; A. A. Bello; D. Habou. Analysis of Wind Energy Potential in North East Nigeria. J. Energy Nat. Resour. 2014, 3(4), 46-50. doi: 10.11648/j.jenr.20140304.11

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AMA Style

A. Ahmed, A. A. Bello, D. Habou. Analysis of Wind Energy Potential in North East Nigeria. J Energy Nat Resour. 2014;3(4):46-50. doi: 10.11648/j.jenr.20140304.11

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@article{10.11648/j.jenr.20140304.11,
  author = {A. Ahmed and A. A. Bello and D. Habou},
  title = {Analysis of Wind Energy Potential in North East Nigeria},
  journal = {Journal of Energy and Natural Resources},
  volume = {3},
  number = {4},
  pages = {46-50},
  doi = {10.11648/j.jenr.20140304.11},
  url = {https://doi.org/10.11648/j.jenr.20140304.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jenr.20140304.11},
  abstract = {This research reports wind energy potential evaluation of two locations in the north east Nigeria (Bauchi and Borno). The evaluation is based on Weibull and Rayleigh models using 17 years mean monthly wind speed data covering the period (1990-2006). The result shows that Rayleigh is best fit model that describes the wind speed data at 10 m height. Reference mean power density (based on the measured probability distribution) was compared with those obtained from the Weibull and Rayleigh models. In calculating the percentage error, results shows that Weibull provided better power density estimation in all 12 months than the Rayleigh model. From this research work, it was found that Borno has high wind power density 273.16 W/m2 for Weibull and 365.77 W/m2 for Rayleigh in the month of June as compared Bauchi with highest power density of 31.45 W/m2 for Weibull and 37.06 W/m2 for Rayleigh in the month of May.},
 year = {2014}
}

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TY  - JOUR
T1  - Analysis of Wind Energy Potential in North East Nigeria
AU  - A. Ahmed
AU  - A. A. Bello
AU  - D. Habou
Y1  - 2014/08/10
PY  - 2014
N1  - https://doi.org/10.11648/j.jenr.20140304.11
DO  - 10.11648/j.jenr.20140304.11
T2  - Journal of Energy and Natural Resources
JF  - Journal of Energy and Natural Resources
JO  - Journal of Energy and Natural Resources
SP  - 46
EP  - 50
PB  - Science Publishing Group
SN  - 2330-7404
UR  - https://doi.org/10.11648/j.jenr.20140304.11
AB  - This research reports wind energy potential evaluation of two locations in the north east Nigeria (Bauchi and Borno). The evaluation is based on Weibull and Rayleigh models using 17 years mean monthly wind speed data covering the period (1990-2006). The result shows that Rayleigh is best fit model that describes the wind speed data at 10 m height. Reference mean power density (based on the measured probability distribution) was compared with those obtained from the Weibull and Rayleigh models. In calculating the percentage error, results shows that Weibull provided better power density estimation in all 12 months than the Rayleigh model. From this research work, it was found that Borno has high wind power density 273.16 W/m2 for Weibull and 365.77 W/m2 for Rayleigh in the month of June as compared Bauchi with highest power density of 31.45 W/m2 for Weibull and 37.06 W/m2 for Rayleigh in the month of May.
VL  - 3
IS  - 4
ER  -

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Author Information

A. Ahmed

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

Department of Mechanical Engineering, Abubakar Tafawa Balewa University, Bauchi, Nigeria
D. Habou

Department of Mechanical Engineering, Abubakar Tafawa Balewa University, Bauchi, Nigeria

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Plain Text BibTeX RIS

APA Style

A. Ahmed, A. A. Bello, D. Habou. (2014). Analysis of Wind Energy Potential in North East Nigeria. Journal of Energy and Natural Resources, 3(4), 46-50. https://doi.org/10.11648/j.jenr.20140304.11

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ACS Style

A. Ahmed; A. A. Bello; D. Habou. Analysis of Wind Energy Potential in North East Nigeria. J. Energy Nat. Resour. 2014, 3(4), 46-50. doi: 10.11648/j.jenr.20140304.11

Copy | Download

AMA Style

A. Ahmed, A. A. Bello, D. Habou. Analysis of Wind Energy Potential in North East Nigeria. J Energy Nat Resour. 2014;3(4):46-50. doi: 10.11648/j.jenr.20140304.11

Copy | Download

@article{10.11648/j.jenr.20140304.11,
  author = {A. Ahmed and A. A. Bello and D. Habou},
  title = {Analysis of Wind Energy Potential in North East Nigeria},
  journal = {Journal of Energy and Natural Resources},
  volume = {3},
  number = {4},
  pages = {46-50},
  doi = {10.11648/j.jenr.20140304.11},
  url = {https://doi.org/10.11648/j.jenr.20140304.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jenr.20140304.11},
  abstract = {This research reports wind energy potential evaluation of two locations in the north east Nigeria (Bauchi and Borno). The evaluation is based on Weibull and Rayleigh models using 17 years mean monthly wind speed data covering the period (1990-2006). The result shows that Rayleigh is best fit model that describes the wind speed data at 10 m height. Reference mean power density (based on the measured probability distribution) was compared with those obtained from the Weibull and Rayleigh models. In calculating the percentage error, results shows that Weibull provided better power density estimation in all 12 months than the Rayleigh model. From this research work, it was found that Borno has high wind power density 273.16 W/m2 for Weibull and 365.77 W/m2 for Rayleigh in the month of June as compared Bauchi with highest power density of 31.45 W/m2 for Weibull and 37.06 W/m2 for Rayleigh in the month of May.},
 year = {2014}
}

Copy | Download

TY  - JOUR
T1  - Analysis of Wind Energy Potential in North East Nigeria
AU  - A. Ahmed
AU  - A. A. Bello
AU  - D. Habou
Y1  - 2014/08/10
PY  - 2014
N1  - https://doi.org/10.11648/j.jenr.20140304.11
DO  - 10.11648/j.jenr.20140304.11
T2  - Journal of Energy and Natural Resources
JF  - Journal of Energy and Natural Resources
JO  - Journal of Energy and Natural Resources
SP  - 46
EP  - 50
PB  - Science Publishing Group
SN  - 2330-7404
UR  - https://doi.org/10.11648/j.jenr.20140304.11
AB  - This research reports wind energy potential evaluation of two locations in the north east Nigeria (Bauchi and Borno). The evaluation is based on Weibull and Rayleigh models using 17 years mean monthly wind speed data covering the period (1990-2006). The result shows that Rayleigh is best fit model that describes the wind speed data at 10 m height. Reference mean power density (based on the measured probability distribution) was compared with those obtained from the Weibull and Rayleigh models. In calculating the percentage error, results shows that Weibull provided better power density estimation in all 12 months than the Rayleigh model. From this research work, it was found that Borno has high wind power density 273.16 W/m2 for Weibull and 365.77 W/m2 for Rayleigh in the month of June as compared Bauchi with highest power density of 31.45 W/m2 for Weibull and 37.06 W/m2 for Rayleigh in the month of May.
VL  - 3
IS  - 4
ER  -

Copy | Download