Goodness of Fit Test for Wind Energy Potential Using Five Distribution Functions for Some Selected in Nigeria

This study focused on goodness of fit test of wind energy potentials for Katsina, Sokoto, Bauchi, Maiduguri, Abuja, Jos, Abeokuta, Lagos, Enugu, Owerri, Calabar and Benin City respectively. Twenty Years (2000-2020) average wind speed data obtained from National Aeronautics and Space Administration (NASA), website using a Renewable Energy Online Software REXSCREEN were analysed. The wind speed data for the selected stations was fitted with five distribution functions such as (normal, Weibull, Rayleigh, lognormal and Gamma Function) with fixed shape parameter (K), but different scale parameters (C). The results of goodness of fit test based on Kolmogorov-Smirnov and Anderson – Darling; shows that all the  probability distribution functions are accepted at maximum difference,   less than their critical values,  (= 0.0853 and 0.0855). While in the AD tests, all the distribution functions hold except lognormal distribution function which is satisfactory for Jos and Abuja with an observed significant level (OSL) ranging from (0.7497 – 0.7497). Therefore, in computing wind power density of the selected cities, the power density empirical model based on normal distribution can be used for Katsina, Sokoto, Bauchi, Maiduguri, Abeokuta, Lagos, Enugu, Owerri, Calabar and Benin city respectively, while in Jos and Abuja, power density based on lognormal can be used for the purpose of surface wind electrification.

Keywords: Goodness of fit test; A-D test; K-S Test; Wind Power Potential; Normal Distribution; Weibull Distribution; Rayleigh Distribution; Log-Normal Distribution; Gamma Distribution.