DOI: 10.21276/sjpms.2018.5.1.4

Pages: 69-77

Automated weather station was installed at Dundaye area (13.10N) where ground based measurements of average hourly wind speed for a period of one calendar year (June 2016 – May, 2017) was monitored. The measured data was then compared with twenty years daily average wind speed data (1991-2010) obtained from Nigerian Meteorological Agency (NIMET). The two set of data was compared in order to validate the long term data from NIMET, where a reasonable regression coefficient R 2  value of 0.897 was obtained. The validated long term data was then used for the wind energy analysis for power generation and identification of the most suitable Wind Energy Conversion System (WECS) for the location, using Weibull probability distribution function. Wind speed pattern, extractable wind power, wind speed carrying maximum energy and most probable wind speed for the location was computed. Similarly, expected Power output was also simulated using the characteristics of a 0.30, 0.23, 0.20 and 1.50 kW WECS from different manufacturers and Weibull parameters evaluated for the location. It was observed that the NE-2000 WECS is the most suitable system that produce optimum results for electricity generation at the location, with capacity factor of 0.36 while Bonus-3000 is the least suitable for the location with capacity factor of 0.06 among the nine WECS selected for the analysis.