Estimation of Wind Energy Potential for Two Locations in North-East Region of Nigeria

Abdullahi Ahmed; Bashir Isyaku Kunya

doi:doi:10.11648/j.jenr.20200902.15

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Estimation of Wind Energy Potential for Two Locations in North-East Region of Nigeria

Abdullahi Ahmed, Bashir Isyaku Kunya

Published in Journal of Energy and Natural Resources (Volume 9, Issue 2)

Received: 29 February 2020 Accepted: 26 March 2020 Published: 13 July 2020

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Abstract

This paper presents an estimation of wind power potential of North East, Nigeria (Bauchi and Maiduguri) on the basis of monthly wind speed data at 10m height from the ground. The data for the locations were collected from Nigeria metrological station, Abuja for the period of (2013-2017). Mean monthly values were used in calculation of Weibull distribution parameters c (scale factor ms^-1) and k (shape factor). The Weibull results shows that for Bauchi, the shape factor ranges from 2.86 – 5.96 and scale factor ranges from 2.32ms^-1 – 2.54ms^-1 while Maiduguri the shape factor ranges from 2.66 – 5.52 and values of scale factor ranges from 4.74ms^-1 – 5.89ms^-1. It is evident that the maximum average monthly value of wind speed in Bauchi occurs in year 2017 with value of 3.8ms^-1 in the month of May while the maximum average wind speed in Maiduguri occurs in year 2013 with value of 8.5ms^-1 in the month of December. The probability distribution function f(V) of wind speed, together with the duration function T(V) was evaluated for the period under investigation. From the statistical analysis of distributions, the Weibull distribution was found to have better fittings in the probability distribution functions f(V) and T(V). The value of power density was computed to be 33.47W/m² (class I) & 374.62W/m² (class II) and energy density was also computed to be 24.9 kWh/m² & 278kWh/m² for both Bauchi and Maiduguri respectively.

Published in	Journal of Energy and Natural Resources (Volume 9, Issue 2)
DOI	10.11648/j.jenr.20200902.15
Page(s)	81-87
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), 2020. Published by Science Publishing Group

Keywords

Weibull Distribution, Weibull Parameters, Duration Function, Wind Energy

References

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[4]	N. Emmani, H. Behbahani-Nia, “The statistical evaluation of wind speed and power density in the Firouzkouh region in Iran”. Taylor and Francis, Vol. 34 (12) pp. 1076-1083 (2013).
[5]	A. N. Celik, “A statistical analysis of wind power density based on the Weibull and Rayleigh Models at the southern region of Turkey”. Renewable Energy, Vol. 29 (5) pp. 593-604 (2004).
[6]	M. J. Stevens, P. T. Smulders, “The estimation of the parameters of the Weibull wind speed distribution for wind energy utilization purposes” Wind Engineering, Vol. 3 (2) pp. 132-84 (1979).
[7]	S. A. Ahmed “Investigation of wind characteristics and wind energy potential at Ras Ghareb, Egypt” Renewable and Sustainable, Energy Reviews, Vol. 5 (2) pp. 2750-2755 (2003).
[8]	Z. Durisic, J. Mikulovic, “Assessment of the wind energy resource in the south Banat region Serbia”, Renewable and Sustainable Energy Reviews, Vol. 16 (4) pp. 3014-3023 (2012).
[9]	M. A Alsaad, “Wind energy potential in selected areas of Jordan”, Energy Conversion and Management, Vol. 65 (10) pp. 704-708 (2013).
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APA Style

Abdullahi Ahmed, Bashir Isyaku Kunya. (2020). Estimation of Wind Energy Potential for Two Locations in North-East Region of Nigeria. Journal of Energy and Natural Resources, 9(2), 81-87. https://doi.org/10.11648/j.jenr.20200902.15

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ACS Style

Abdullahi Ahmed; Bashir Isyaku Kunya. Estimation of Wind Energy Potential for Two Locations in North-East Region of Nigeria. J. Energy Nat. Resour. 2020, 9(2), 81-87. doi: 10.11648/j.jenr.20200902.15

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AMA Style

Abdullahi Ahmed, Bashir Isyaku Kunya. Estimation of Wind Energy Potential for Two Locations in North-East Region of Nigeria. J Energy Nat Resour. 2020;9(2):81-87. doi: 10.11648/j.jenr.20200902.15

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@article{10.11648/j.jenr.20200902.15,
  author = {Abdullahi Ahmed and Bashir Isyaku Kunya},
  title = {Estimation of Wind Energy Potential for Two Locations in North-East Region of Nigeria},
  journal = {Journal of Energy and Natural Resources},
  volume = {9},
  number = {2},
  pages = {81-87},
  doi = {10.11648/j.jenr.20200902.15},
  url = {https://doi.org/10.11648/j.jenr.20200902.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jenr.20200902.15},
  abstract = {This paper presents an estimation of wind power potential of North East, Nigeria (Bauchi and Maiduguri) on the basis of monthly wind speed data at 10m height from the ground. The data for the locations were collected from Nigeria metrological station, Abuja for the period of (2013-2017). Mean monthly values were used in calculation of Weibull distribution parameters c (scale factor ms-1) and k (shape factor). The Weibull results shows that for Bauchi, the shape factor ranges from 2.86 – 5.96 and scale factor ranges from 2.32ms-1 – 2.54ms-1 while Maiduguri the shape factor ranges from 2.66 – 5.52 and values of scale factor ranges from 4.74ms-1 – 5.89ms-1. It is evident that the maximum average monthly value of wind speed in Bauchi occurs in year 2017 with value of 3.8ms-1 in the month of May while the maximum average wind speed in Maiduguri occurs in year 2013 with value of 8.5ms-1 in the month of December. The probability distribution function f(V) of wind speed, together with the duration function T(V) was evaluated for the period under investigation. From the statistical analysis of distributions, the Weibull distribution was found to have better fittings in the probability distribution functions f(V) and T(V). The value of power density was computed to be 33.47W/m2 (class I) & 374.62W/m2 (class II) and energy density was also computed to be 24.9 kWh/m2 & 278kWh/m2 for both Bauchi and Maiduguri respectively.},
 year = {2020}
}

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TY  - JOUR
T1  - Estimation of Wind Energy Potential for Two Locations in North-East Region of Nigeria
AU  - Abdullahi Ahmed
AU  - Bashir Isyaku Kunya
Y1  - 2020/07/13
PY  - 2020
N1  - https://doi.org/10.11648/j.jenr.20200902.15
DO  - 10.11648/j.jenr.20200902.15
T2  - Journal of Energy and Natural Resources
JF  - Journal of Energy and Natural Resources
JO  - Journal of Energy and Natural Resources
SP  - 81
EP  - 87
PB  - Science Publishing Group
SN  - 2330-7404
UR  - https://doi.org/10.11648/j.jenr.20200902.15
AB  - This paper presents an estimation of wind power potential of North East, Nigeria (Bauchi and Maiduguri) on the basis of monthly wind speed data at 10m height from the ground. The data for the locations were collected from Nigeria metrological station, Abuja for the period of (2013-2017). Mean monthly values were used in calculation of Weibull distribution parameters c (scale factor ms-1) and k (shape factor). The Weibull results shows that for Bauchi, the shape factor ranges from 2.86 – 5.96 and scale factor ranges from 2.32ms-1 – 2.54ms-1 while Maiduguri the shape factor ranges from 2.66 – 5.52 and values of scale factor ranges from 4.74ms-1 – 5.89ms-1. It is evident that the maximum average monthly value of wind speed in Bauchi occurs in year 2017 with value of 3.8ms-1 in the month of May while the maximum average wind speed in Maiduguri occurs in year 2013 with value of 8.5ms-1 in the month of December. The probability distribution function f(V) of wind speed, together with the duration function T(V) was evaluated for the period under investigation. From the statistical analysis of distributions, the Weibull distribution was found to have better fittings in the probability distribution functions f(V) and T(V). The value of power density was computed to be 33.47W/m2 (class I) & 374.62W/m2 (class II) and energy density was also computed to be 24.9 kWh/m2 & 278kWh/m2 for both Bauchi and Maiduguri respectively.
VL  - 9
IS  - 2
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. (2020). Estimation of Wind Energy Potential for Two Locations in North-East Region of Nigeria. Journal of Energy and Natural Resources, 9(2), 81-87. https://doi.org/10.11648/j.jenr.20200902.15

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ACS Style

Abdullahi Ahmed; Bashir Isyaku Kunya. Estimation of Wind Energy Potential for Two Locations in North-East Region of Nigeria. J. Energy Nat. Resour. 2020, 9(2), 81-87. doi: 10.11648/j.jenr.20200902.15

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AMA Style

Abdullahi Ahmed, Bashir Isyaku Kunya. Estimation of Wind Energy Potential for Two Locations in North-East Region of Nigeria. J Energy Nat Resour. 2020;9(2):81-87. doi: 10.11648/j.jenr.20200902.15

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@article{10.11648/j.jenr.20200902.15,
  author = {Abdullahi Ahmed and Bashir Isyaku Kunya},
  title = {Estimation of Wind Energy Potential for Two Locations in North-East Region of Nigeria},
  journal = {Journal of Energy and Natural Resources},
  volume = {9},
  number = {2},
  pages = {81-87},
  doi = {10.11648/j.jenr.20200902.15},
  url = {https://doi.org/10.11648/j.jenr.20200902.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jenr.20200902.15},
  abstract = {This paper presents an estimation of wind power potential of North East, Nigeria (Bauchi and Maiduguri) on the basis of monthly wind speed data at 10m height from the ground. The data for the locations were collected from Nigeria metrological station, Abuja for the period of (2013-2017). Mean monthly values were used in calculation of Weibull distribution parameters c (scale factor ms-1) and k (shape factor). The Weibull results shows that for Bauchi, the shape factor ranges from 2.86 – 5.96 and scale factor ranges from 2.32ms-1 – 2.54ms-1 while Maiduguri the shape factor ranges from 2.66 – 5.52 and values of scale factor ranges from 4.74ms-1 – 5.89ms-1. It is evident that the maximum average monthly value of wind speed in Bauchi occurs in year 2017 with value of 3.8ms-1 in the month of May while the maximum average wind speed in Maiduguri occurs in year 2013 with value of 8.5ms-1 in the month of December. The probability distribution function f(V) of wind speed, together with the duration function T(V) was evaluated for the period under investigation. From the statistical analysis of distributions, the Weibull distribution was found to have better fittings in the probability distribution functions f(V) and T(V). The value of power density was computed to be 33.47W/m2 (class I) & 374.62W/m2 (class II) and energy density was also computed to be 24.9 kWh/m2 & 278kWh/m2 for both Bauchi and Maiduguri respectively.},
 year = {2020}
}

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TY  - JOUR
T1  - Estimation of Wind Energy Potential for Two Locations in North-East Region of Nigeria
AU  - Abdullahi Ahmed
AU  - Bashir Isyaku Kunya
Y1  - 2020/07/13
PY  - 2020
N1  - https://doi.org/10.11648/j.jenr.20200902.15
DO  - 10.11648/j.jenr.20200902.15
T2  - Journal of Energy and Natural Resources
JF  - Journal of Energy and Natural Resources
JO  - Journal of Energy and Natural Resources
SP  - 81
EP  - 87
PB  - Science Publishing Group
SN  - 2330-7404
UR  - https://doi.org/10.11648/j.jenr.20200902.15
AB  - This paper presents an estimation of wind power potential of North East, Nigeria (Bauchi and Maiduguri) on the basis of monthly wind speed data at 10m height from the ground. The data for the locations were collected from Nigeria metrological station, Abuja for the period of (2013-2017). Mean monthly values were used in calculation of Weibull distribution parameters c (scale factor ms-1) and k (shape factor). The Weibull results shows that for Bauchi, the shape factor ranges from 2.86 – 5.96 and scale factor ranges from 2.32ms-1 – 2.54ms-1 while Maiduguri the shape factor ranges from 2.66 – 5.52 and values of scale factor ranges from 4.74ms-1 – 5.89ms-1. It is evident that the maximum average monthly value of wind speed in Bauchi occurs in year 2017 with value of 3.8ms-1 in the month of May while the maximum average wind speed in Maiduguri occurs in year 2013 with value of 8.5ms-1 in the month of December. The probability distribution function f(V) of wind speed, together with the duration function T(V) was evaluated for the period under investigation. From the statistical analysis of distributions, the Weibull distribution was found to have better fittings in the probability distribution functions f(V) and T(V). The value of power density was computed to be 33.47W/m2 (class I) & 374.62W/m2 (class II) and energy density was also computed to be 24.9 kWh/m2 & 278kWh/m2 for both Bauchi and Maiduguri respectively.
VL  - 9
IS  - 2
ER  -

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