On the Remapping and Identification of  Potential Wind Sites in Nigeria

Zaccheus O. Olaofe

doi:10.4236/epe.2015.710046

Home > Journals > Engineering > EPE

Energy and Power Engineering > Vol.7 No.10, September 2015

On the Remapping and Identification of Potential Wind Sites in Nigeria ()

Zaccheus O. Olaofe

Climate System and Analysis Group, University of Cape Town, Rondebosch, South Africa.

DOI: 10.4236/epe.2015.710046 PDF HTML 4,086 Downloads 4,510 Views Citations

Abstract

The ERA-Interim reanalysis wind based on the distance-weighted average remapping for studying the wind circulation in Nigeria is presented. The wind flow using this atmospheric model simulation is studied for identification of grid-tie electrification opportunities in different wind locations. A 10-year reanalysis wind speed components at a surface level of the planetary layer at 0.25° × 0.25° spatial resolution is obtained and remapped into a new horizontal wind field at a grid resolution of 0.125° × 0.125° covering longitudinal and latitudinal directions of 3.0 - 15.0°E and 15.0 - 3.0°N, respectively. Using the distance-weighted average technique, the remapped wind field at a new grid resolution of 0.125° × 0.125° is compared at different terrain elevations and approximated close to the actual wind field of the same resolution. To determine the suitability of the prevailing wind for small-scale energy conversion, the magnitude of wind flow across the remapped wind field is studied for a 10-year period. Analysis shows that northern regions of Nigeria have a fair wind potential for a stand-alone application based on the wind flow originated at Gulf of Guinea as well as Chad and Niger. Furthermore, hourly surface wind speed observations from 18 synoptic stations in Nigeria are obtained and compared with the bilinear interpolated wind stations. The reanalysis wind reflects the surface wind observations and proves that the prevailing wind in Nigeria is higher than the reanalysis wind projection obtained from gridded data at resolution of 0.125° × 0.125°. The sectorwise wind directions at each synoptic stations for a period of 10 years are presented.

Keywords

ERA-Interim Wind Components, Grid Resolutions, Relative Error, Distance-Weighted Remapping, Bilinear Interpolation, Nigeria

Share and Cite:

Olaofe, Z. (2015) On the Remapping and Identification of Potential Wind Sites in Nigeria. Energy and Power Engineering, 7, 477-499. doi: 10.4236/epe.2015.710046.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	Nilsson, K. and Ivanell, S. (2010) Wind Energy. Gotland University, Visby.
[2]	Aidan, J. and Ododo, J.C. (2010) Wind Speed Distributions and Power Densities of Some Cities in Northern Nigeria. Journal of Engineering and Applied Sciences, 5, 420-426. http://dx.doi.org/10.3923/jeasci.2010.420.426
[3]	Ohunakin, O.S. (2011) Wind Characteristics and Wind Energy Potential Assessment in Uyo, Nigeria. Journal of Engineering and Applied Sciences, 6, 141-146. http://dx.doi.org/10.3923/jeasci.2011.141.146
[4]	Ojosu, J.O. and Salawu R.I. (1990) Wind Energy Development in Nigeria. Nigerian Journal of Solar Energy, 9, 29-32.
[5]	Ojosu, J.O. and Salawu R.I. (1990) Survey of Wind Energy Potential in Nigeria. Solar & Wind Technology, 7, 155-167. http://dx.doi.org/10.1016/0741-983X(90)90083-E
[6]	Adekoya, L.O. and Adewale, A.A. (1992) Wind Energy Potential of Nigeria. Renewable Energy, 2, 35-39. http://dx.doi.org/10.1016/0960-1481(92)90057-A
[7]	Anyanwu, E.E. and Iwuagwu, C.J. (1995) Wind Characteristics and Energy Potentials for Owerri, Nigeria. Renewable Energy, 6, 125-128. http://dx.doi.org/10.1016/0960-1481(94)00028-5
[8]	Agbaka, A.C. (1987) Experimental Investigation of the Possible Correction of Wind Speed on Insolation. Energy Conversion & Management, 27, 45-48. http://dx.doi.org/10.1016/0196-8904(87)90051-3
[9]	Igbokwe, M.U. and Omekara C.O. (2002) Stochastic Simulation of Hourly Average Wind Speed in Umudike, South-East Nigeria. Global Journal of Mathematical Sciences, 1, 59-66. http://dx.doi.org/10.4314/gjmas.v1i1.21323
[10]	Medugu, D.W. and Malgwi, D.I. (2005) A Study of Wind Energy Potential: Remedy for Fluctuation of Electric Power in Mubi, Adamawa State, Nigeria. Nigerian Journal of Physics, 17, 40-45.
[11]	Ngala, G.M., Alkali, B. and Aji, M.A. (2007) Viability of Wind Energy as a Power Generation Source in Maiduguri, Borno State, Nigeria. Renewable Energy, 32, 2242-2246. http://dx.doi.org/10.1016/j.renene.2006.12.016
[12]	Oriaku, C.I., Osuwa, J.C., Asiegbu, A.D., Chukwu, G.U. and Kanu, C.O. (2007) Frequency Distribution Analysis of Available Wind Resources in Umudike, Abia State, Nigeria, for Wind Energy Conversion System Design. Pacific Journal of Science & Technology, 8, 203-206.
[13]	Garba, A.D. and Al-Amin, M. (2014) Assessment of Wind Energy Alternative in Nigeria from the Lessons of the Katsina Wind Farm. Civil and Environmental Research, 6, 91-94.
[14]	Pedersen, B.M., Hansen, K.S., Øye, S., Brinch, M. and Fabian, O. (1992) Some Experimental Investigations on the Influence of the Mounting Arrangements on the Accuracy of Cup—Anemometer Measurements. Journal of Wind Engineering and Industrial Aerodynamics, 39, 373-383. http://dx.doi.org/10.1016/0167-6105(92)90561-N
[15]	(2010) Best Practice Guidelines for Mesoscale Wind Mapping Projects for the World Bank. 1-40.
[16]	Petersen, E.L., Mortensen, N.G., Landberg, L., Højstrup, J. and Frank, H.P. (1998) Wind Power Meteorology. Part II: Siting and Models. Wind Energy, 1, 55-72. http://dx.doi.org/10.1002/(SICI)1099-1824(199812)1:2<55::AID-WE5>3.0.CO;2-R
[17]	Dee, D.P., Uppalaa, S.M., Simmonsa, A.J., Berrisford, P., Poli, P., Kobayashib, S., Andraec, U., Balmaseda, M.A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A.C.M., van de Bergd, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A.J., Haimbergere, L., Healy, S.B., Hersbach, H., Hólm, E.V., Isaksen, L., Kållberg, P., Köhler, M., Matricardia, M., McNally, A.P., Monge-Sanz, B.M., Morcrettea, J.-J., Park, B.-K., Peubeya, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N. and Vitarta, F. (2011) The ERA-Interim Reanalysis: Configuration and Performance of the Data Assimilation System. Quarterly Journal of the Royal Meteorological Society, 137, 553-597. http://dx.doi.org/10.1002/qj.828
[18]	Lavagnini, A., Sempreviva, A.M., Transerici, C., Accadia, C., Casaioli, M., Mariani, S. and Speranza, A. (2006) Offshore Wind Climatology over the Mediterranean Basin. Wind Energy, 9, 251-266. http://dx.doi.org/10.1002/we.169
[19]	Jimenez, B., Durante, F., Lange, B., Kreutzer, T. and Tambke, J. (2007) Offshore Wind Resource Assessment with WAsP and MM5: Comparative Study for the German Bight. Wind Energy, 10, 121-134. http://dx.doi.org/10.1002/we.212
[20]	Buzzi, A., Fantini, M., Malguzzi, P. and Nerozzi, F. (1994) Validation of a Limited Area Model in Cases of Mediterranean Cyclogenesis: Surface Fields and Precipitation Scores. Meteorology and Atmospheric Physics, 53, 53-67. http://dx.doi.org/10.1007/BF01029609
[21]	http://apps.ecmwf.int/datasets/data/interim_full_daily/
[22]	http://www.ncdc.noaa.gov/
[23]	Lucchesi, R. (2008) File Specification for MERRA Products. Global Modeling and Assimilation Office Report, Version 2.1, 8.
[24]	Fadare, D.A. (2008) A Statistical Analysis of Wind Energy Potential in Ibadan, Nigeria, Based on Weibull Distribution Function. Pacific Journal of Science and Technology, 9, 110-119.