Abstract
The objective of this study was to assess the potential viability of the wind resource potential in Jos, Plateau state, Nigeria for power generation. The monthly mean wind speeds that span from 1987 to 2007 were employed to statistically analyze the monthly, annual and seasonal potentials of the wind energy resources at the site. Besides, the results were employed together with two models of wind energy conversion system to simulate the likely average output power. The outcome showed that Jos was suitable as a site for wind farm projects of varying sizes and that MW·h to GW·h of electricity is likely to be produced per period of months, seasons and years. The average wind speed range at the site was also estimated to be between 6.7 and 11.8 m/s across the months, years and seasons.
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Youm I, Sarr J, Sall M, Ndiaye A, Kane MM. Analysis of wind data and wind energy potential along the northern coast of Senegal. Renewable Energy Review, 2005, 8: 95–108
Sørensen H C, Larsen J H, Olsen F A, Svenson J, Hansen S R. Middelgrunden 40MW offshore wind farm, a prestudy for the Danish offshore 750MW wind program. In: Proceedings of 10th ISOPE Conference. Seattle, USA, 2000
Manwell J F, Rogers A, McGowan J G. Assessment of the massachusetts offshore wind energy resource. In: European Wind Energy Conference. Copenhagen, 2001
Henderson A R, Morgan C, Barthelmie R, Smith B, Sørensen H C, Boesmans B. Offshore wind energy—Review of the state-of-the-art. In: Proceedings of the 12th International Offshore and Polar Engineering Conference. Kitakyushu, Japan, 2002, 494–498
Stiebler M. Wind Energy Systems for Electric Power Generation. Berlin: Springer, 2008
Ajayi O O. The potential for wind energy in Nigeria. Wind Engineering, 2010, 34(3): 303–311
Energy Commission of Nigeria and United Nations Development Programme (ECN-UNDP). Renewable Energy Master Plan: Final Draft Report. 2007-06-17, http://www.iceednigeria.org/REMP%20Final%20Report.pdf
Federal Ministry of Power and Steel. Federal Republic of Nigeria. Renewable Electricity Action Porgramme (REAP). 2010-10-01, http://www.iceednigeria.org/REAP-postconference.pdf
Ajayi O O. Assessment of utilization of wind energy resources in Nigeria. Energy Policy, 2009, 37(2): 720–723
Asiegbu A D, Iwuoha G S. Studies of wind resources in Umudike, South East Nigeria — An assessment of economic viability. Journal of Engineering and Applied Sciences, 2007, 2(10): 1539–1541
Fadare D A. A Statistical analysis of wind energy potential in Ibadan, Nigeria, based on Weibull distribution function. Pacific Journal of Science and Technology, 2008, 9(1): 110–119
Ogbonnaya I O, Chikuni E, Govender P. Prospect of Wind Energy in Nigeria. 2009-07-16, http://active.cput.ac.za/energy/web/due/papers/2007/023O_Okoro.pdf
Fadare D A. The application of artificial neural networks to mapping of wind speed profile for energy application in Nigeria. Applied Energy, 2010, 87(3): 934–942
Akpabio L E, Udo S O, Etuk S E. Modelling global solar irradiation for a tropical location: Onne, Nigeria. Turkish Journal of Physics, 2005, 29(1): 63–68
Keyhani A, Ghasemi-Varnamkhasti M, Khanali M, Abbaszadeh R. An assessment of wind energy potential as a power generation source in the capital of Iran, Tehran. Energy, 2010, 35(1): 188–201
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
Carta J A, Ramı’rez P, Vela’zquez S. A review of wind speed probability distributions used in wind energy analysis. Renewable & Sustainable Energy Reviews, 2009, 13(5): 933–955
Murthy D N P, Xie M, Jiang R. Weibull Models (Wiley Series in Probability and Statistics). New Jersey: Wiley, 2004
Izquierdo D, Alonso C, Andrade C, Castellote M. Potentiostatic determination of chloride threshold values for rebar depassivation: Experimental and statistical study. Electrochimica Acta, 2004, 49(17,18): 2731–2739
Roberge P R. Statistical Interpretation of Corrosion Test Results. In: Corrosion: Fundamentals, Testing, and Protection, ASM Handbook, Vol 13A. Russell Township, USA: ASM International, 2003, 425–429
Roberge P R. Handbook of Corrosion Engineering. New York: McGraw-Hill, 2000
Omotosho O A, Okeniyi J O, Ajayi O O. Performance evaluation of potassium dichromate and potassium chromate inhibitors on concrete steel rebar corrosion. Journal of Failure Analysis and Prevention, 2010, 10(5): 408–415
Polyanin A D, Manzhirov A V. Handbook of Mathematics for Engineers and Scientists. Boca Raton: Chapman & Hall/CRC, 2007
Soong T T. Fundamentals of Probability and Statistics for Engineers. England: Wiley, 2004
Lipson C, Sheth N J. Statistical Design and Analysis of Engineering Experiments. New York: McGraw-Hill, 1973
Montgomery D C, Runger G C. Applied Statistics and Probability for Engineers. 3rd ed. New Jersey: Wiley, 2003
Krause P, Boyle D P, Bäse F. Comparison of different efficiency criteria for hydrological model assessment. Advances in Geosciences, 2005, 5: 89–97
Fagbenle R O, Katende J, Ajayi O O, Okeniyi J O. Assesment of wind energy potential of two sites in North-East, Nigeria. Renewable Energy, 2011, 36(4): 1277–1283
Energy G E. 1.5MW Wind Turbine. 2010-09-29, http://www.geenergy.com/prod_serv/products/wind_turbines/en/downloads/GEA14954C15-MW-Broch.pdf
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Ajayi, O.O., Fagbenle, R.O., Katende, J. et al. Availability of wind energy resource potential for power generation at Jos, Nigeria. Front. Energy 5, 376–385 (2011). https://doi.org/10.1007/s11708-011-0167-5
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DOI: https://doi.org/10.1007/s11708-011-0167-5