GOODNESS OF FIT TEST FOR WIND ENERGY POTENTIAL USING FIVE PROBABILITY DENSITY FUNCTIONS FOR SOME SELECTED CITIES IN NIGERIA
DOI:
https://doi.org/10.33003/fjs-2022-0601-882Keywords:
Goodness of fit test; A-D test; K-S Test; Wind Power Potential and Probability distribution functionsAbstract
This research gives a better understanding on wind energy availability for some selected cities in Nigeria, such as 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 NIMET Headquarters Abuja, were analysed and fitted with five probability density functions such as normal, Weibull, Rayleigh, lognormal and Gamma Function with fixed shape parameter (K), but different scale parameters (C) in the model. 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 A-D 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, this results can be used for investors on wind power and also improve wind farm project for surface wind electrification
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