Abstract
The wind energy potential at Ikeja (Lat. 6.35 N; Long. 3.20 E), Nigeria was statistically analyzed using three of the mostly utilized conventional Probability Distribution Functions (PDFs) in order to determine which of these distributions would give the best means of analysis for wind in this particular location. The best fit test for these PDFs were determined from Akaike Information Criteria, Bayesian Information Criteria, Kolmogorov-Smirnov test, Cramer-von Mises statistics, Anderson-Darling Statistic, Mean Square Error and Chi-Square Test using Maximum Likelihood Estimation and Method of Moments as parameter estimates. The Weibull distribution gave the best fit in this location.
Highlights
Wind is a renewable form of energy which is abundant in many parts of the world [1].The reasons for the development of wind as a renewable source of energy include higher demand and decline in fossil fuel reserves including the global warming issues associated with the fossil fuel utilization [2]
In the earlier works on statistical modeling of wind speed variation, much consideration has been given to the two-parameter Weibull distribution because it has been found to fit a wide collection of wind data [5]
The results of the various methods of determining the goodness of fit tests for the conventional Probability Density Functions (PDFs) showed that the Weibull distribution gave the best estimates in terms of efficiency of performance amongst the three (3) distributions considered
Summary
Wind is a renewable form of energy which is abundant in many parts of the world [1].The reasons for the development of wind as a renewable source of energy include higher demand and decline in fossil fuel reserves including the global warming issues associated with the fossil fuel utilization [2]. Wind speed which is the movement of air in the atmosphere at a particular time is a random variable and is usually measured using anemometer. The modeling of wind speed variation is an essential requirement in the estimation of wind energy for any particular location [4]. In the earlier works on statistical modeling of wind speed variation, much consideration has been given to the two-parameter Weibull distribution (shape parameter and scale parameter) because it has been found to fit a wide collection of wind data [5]. Other probability density functions apart from that of Weibull including Gamma and Lognormal shall be included in the analysis utilized in this work in order to be able to determine how well they too could accurately fit the wind speed data in this location
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