Comparative characterization study of the variability of wind energy potential by wind direction sectors for three coastal sites in Lomé, Accra and Cotonou

Ayite Senah Akoda Ajavon, Akim A. Salami, Mawugno K. Kodjo, Koffi-Sa Bédja

Abstract


This paper presents the characterization of the distribution of wind speeds across sectors of directions in order to study
the variability of wind energy potential on sites in Lomé (Togo), Accra (Ghana) and Cotonou (Benin) in the Gulf of
Guinea. To this end, we developed a software application in MATLAB aimed at wind data processing. Each site’s wind
speed data collected over a period from January 2000 to December 2012 at a height of 10 m above the ground were
divided into eight sectors of direction of 45 degrees each, according to the wind directions measured. Parameters such
as K (shape factor) and C (scale factor) of Weibull distributions as well as the skewness and kurtosis coecients were
obtained for each sector. The study analyzes the variations of the statistical parameters computed based on the number
of hours during which wind blows in each sector of direction. The results show that the South and South-West sectors
are areas of prevailing winds and have higher wind energy potential compared to other sectors in general on the 3 sites
considered. The more frequent the wind blows in a sector of direction, the higher the Weibull parameters, while the
coecients of skewness and kurtosis of the distributions of wind speeds show a downward trend for all 3 sites.

Keywords


Wind energy potential, Weibull Distribution, Compass rose, Modeling

Full Text:

PDF

References


A. Judzinska-Kłodawska, Selected aspects of material and energy model assessment of onshore and offshore wind farms, Journal of Power Technologies, 93 (5) (2013) 407-412.

Torres J. L. Garcia A. Prieto E. and De Fransisco A., Characterization of wind speed data according to wind direction, Solar Energy Vol. 66, No1, pp 57-64, Elsevier Science Ltd, 1999.

A. Islam, S. R. Hasib, M. S. Islam,, Short term electricity demand forcasting of an isolated area using two different aproach, Journal of Power Technologies, 93 (4) (2013) 185-193.

Salami A. A., Ajavon A. S. A., Kodjo K. M., Bedja K., Contribution to improving the modeling of wind and evaluation of the wind potential of the site of Lome: Problems of taking into account the frequency of calm winds, Elsevier, Renewable Energy 50 (2013) 449-455.

http://Wheather.uwyo.edu/surface/meteogram/.

Seguro, J. V., and T. W. Lambert, 2000: Modern estimation of the parameters of the Weibull wind speed distribution for wind energy analysis. J. Wind Eng. Ind. Aerodyn., 85, 75–84.

Hacene F. Boukli N. Kasbadji M. and Loukarfi L., Statistical analysis and development of a wind atlas for the Cheliff’s valley, Journal of Renewable Energies Vol. 10 N°4 (2007) 583 – 588, University of Hassiba Ben Bouali, Algeria.

Fichaux N., Evaluation of the offshore wind energy potential and satellite imagery. PhD thesis, Ecole des Mines de Paris, December 2003.


Refbacks

  • There are currently no refbacks.