In this study, the performance of three global solar radiation models and the accuracy of global solar radiation data derived from three sources were compared. Twenty-two years of surface meteorological data consisting of monthly mean daily sunshine duration, minimum and maximum temperatures, and global solar radiation collected from the Nigerian Meteorological (NIMET) Agency, Oshodi, Lagos, and the National Aeronautics Space Agency (NASA) for three locations in North-Western region of Nigeria were used. A new model incorporating Garcia model into Angstrom-Prescott model was proposed for estimating global radiation in Nigeria. The performances of the models used were determined by using mean bias error (MBE), mean percentage error (MPE), root mean square error (RMSE), and coefficient of determination ( 2 ). Based on the statistical error indices, the proposed model was found to have the best accuracy with the least RMSE values (0.376 for Sokoto, 0.463 for Kaduna, and 0.449 for Kano) and highest coefficient of determination, 2 values of 0.922, 0.938, and 0.961 for Sokoto, Kano, and Kaduna, respectively. Also, the comparative study result indicates that the estimated global radiation from the proposed model has a better error range and fits the ground measured data better than the satellite-derived data.

This study assesses the wind-energyresources in Nigeria by reviewing the existing literature on the subject matter, and also evaluates the wind potential in six locations in the northwest region of the country. Twenty-two years ' (1984 -2005) wind speed data obtained from the Nigerian Meteorological Agencies (NIMET) were used in this study.Weibull two-parameter and other statistical models were employed in this analysis. Wind speed distribution across Nigeria shows that some locations in the northern part of the country are endowed with higher wind potential than others in the southern part of the country. Moreover, assessment of the wind-energy resources in the study locations reveals that wind energy potential in the region is lowest in Yelwa and highest in Kano; WPD varies from 28.

In this study, the predictive ability of two-parameter Weibull distribution function in analyzing wind speed data was assessed in two selected sites with different mean wind speeds in the North-Western region of Nigeria. Twenty-two years wind speed data spanning from 1984 to 2005 was used in the analysis. The data were obtained from the Nigerian Meteorological Agency (NIMET) in Lagos. The results of the analysis show that Weibull function is suitable for analyzing measured wind speed data and in predicting the wind-power density in both locations and that Weibull function is not discriminative between locations with high and low mean wind speeds in analyzing wind data. The annual mean wind speeds for the two sites (Sokoto and Yelwa) are 7.99 ms-1 and 2.59 ms-1 respectively, while the annual values of the most probable wind speed and the maximum, energy-carrying wind speeds are respectively:3.52 and 4.34 ms-1 for Yelwa and 8.33 and 9.02 ms-1 for Sokoto. The estimated annual wind power densities for Yelwa and Sokoto are respectively 36.91 and 359.96 Wm-2. Therefore, Sokoto has a better prospect for wind power generation.