Evaluation of the wind energy potential of two south west sites in Nigeria

Abstract

Wind resource assessment is a crucial first step in gauging the potential of a site to produce energy from wind turbines. In this paper, the wind energy potential of Abeokuta (07°03'N, 03°19'E) and Ijebu-Ode (06°47'N, 03°58'E), two south west sites in Nigeria were examined. Twenty years (1990–2010) of monthly mean wind data from a 10 m height were subjected to two-parameter Weibull analysis and other statistical analyses. The results show that the average annual mean wind speed variation for Abeokuta ranges from 2.2 to 5.0 m/s. For Ijebu-Ode, it ranges from 2.0 to 5.0 m/s. The wind power density variation based on the Weibull analysis ranges from 4.26 to 24.51 W/m² for Abeokuta and from 8.54 to 76.46 W/m² for Ijebu-Ode. Ijebu-Ode was found to be the better of the two sites in terms of annual variation of mean wind speed.

Keywords

wind potential / wind speed / wind power density / wind gust / turbulence intensity / Nigeria

References

[1] Fagbenle R L, Karayiannis T G. On the wind energy resource of Nigeria. International Journal of Energy Research, 1994, 18(5): 493-508

[2] Ojosu J O, Salawu R I. An evaluation of wind energy potential as a power generation source in Nigeria. Solar & Wind Technology, 1990, 7(6): 663-673

[3] Adekoya L O, Adewale A A. Wind energy potential of Nigeria. Renewable Energy, 1992, 2(1): 35-39

[4] Spera D A. Wind Turbine Technology: Fundamental Concepts in Wind Turbine Engineering. New York: ASME Press, 1994

[5] Katsoulis B D. A survey on the assessment of wind energy potential in Greece. Theoretical and Applied Climatology, 1993, 47(1): 51-63

[6] Ajayi O O, Fagbenle R O, Katende J, Okeniyi J O, Omotosho O A. Wind energy potential for power generation of a local site in Gusau, Nigeria. International Journal of Energy for a Clean Environment, 2010, 11(1-4): 99-116

[7] Burton T, Sharpe D, Jenkins N, Bossanyi E. Wind Energy Handbook. New York: John Wiley & Sons, Ltd., 2001

[8] Akpinar E K, Akpinar S.An assessment on seasonal analysis of wind energy characteristics and wind turbine characteristics. Energy Conversion and Management, 2005, 46(11,12): 1848-1867

[9] Bagiorgas H S, Assimakopoulos M N, Theoharopoulos D, Matthopoulos D, Mihalakakou G K. Electricity generation using wind energy conversion systems in the area of Western Greece. Energy Conversion and Management, 2007, 48(5): 1640-1655

[10] Mathew S, Pandey K P, Kumar A V. Analysis of wind regimes for energy estimation. Renewable Energy, 2002, 25(3): 381-399

[11] Ucar A, Balo F. Evaluation of wind energy potential and electricity generation at six locations in Turkey. Applied Energy, 2009, 86(10): 1864-1872

[12] Safari B, Gasore J. A statistical investigation of wind characteristics and wind energy potential based on the Weibull and Rayleigh models in Rwanda. Renewable Energy, 2010, 35(12): 2874-2880

[13] Cochran B C. The influence of atmospheric turbulence on the kinetic energy available during small wind turbine power performance testing. 2012-<month>5</month>-<day>5</day>, http://107.22.218.192/support/papers/papers/windenergy/SmallWindTurbineTesting.pdf

[14] Frandsen S, Madsen P H. Spatially average turbulence intensity inside large wind turbine arrays. 2012-<month>5</month>-<day>5</day>, http://www.risoe.dk/vea/recoff/Documents/Sec_3/RECOFFdoc068.pdf

[15] Tattelman P. Surface gustiness and wind speed range as a function of time interval and mean wind speed. Journal of Applied Meteorology, 1975, 14(7): 1271-1276

[16] Davis F K, Newstein H. The variation of gust factors with mean wind speed and with height. Journal of Applied Meteorology, 1968, 7(3): 372-378

[17] Deese J H, Whisenant C C. The Problem of low level wind distribution. Kennedy Space Center, NASA Technical Report, NASA-TM-X-57159. 1964

[18] Greenway M E. An analytical approach to wind velocity gust factors. Journal of Wind Engineering and Industrial Aerodynamics, 1979, 5(1,2): 61-91

[19] Wieringa J. Gust factors over open water and built-up country. Boundary-Layer Meteorology, 1973, 3(4): 424-441

[20] Montgomery D C, Runger G C. Applied Statistics and Probability for Engineers. <BibVersion>3rd ed</BibVersion>. New Jersey: Wiley, 2003

[21] Krause P, Boyle D P, Bäse F. Bäse F. Comparison of different efficiency criteria for hydrological model assessment. Advances in Geosciences, 2005, 5: 89-97

Acknowledgements

Mr. Oluwafemi G. Oyekunle assisted with the data obtained from the Nigerian Meteorological Department for which the author expresses his gratitude.

RIGHTS & PERMISSIONS

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg