Abstract:
In this study, wind energy potential of Moi University site was investigated with a view of looking into the possibility of integrating the institution’s electricity supply with wind power energy. The evaluation was done at 10, 20.2, 29.5, 41.5, 44.3, and 46.3 m height using hourly data obtained for the period January 2010-December 2013. Comparison of two measure-correlate-predict (MCP) algorithms was done using three metrics (mean wind speed, Weibull scale parameter and Weibull shape parameter). The MCP model that gave the best fit was then used to predict missing wind speed data at Moi University. The performance of the Weibull model was assessed by three different parameter evaluation techniques: the root mean square error, chi-square, and the coefficient of determination. The wind speed characteristics for turbine selection (most probable wind speed, wind speed at maximum energy, turbulence intensity and energy pattern factor) were also assessed and the average annual values were found to be 4.074 m/s, 4.320 m/s, 0.163, and 1.28 respectively at 46.3 m hub height. The annual mean air density, mean wind speed, Weibull power density, Weibull shape parameter and Weibull scale parameter were found to be 0.8838 kg/m3, 3.907 m/s, and 36.214 W/m2, 6.962, and 4.166 m/s respectively for the same hub height. The linear regression model gave better predictions than variance ratio model.
