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Performance Probability Distribution Function for Modelling Solar Radiation in South Southern Nigeria: A Case Study of Yenagoa
Author(s) -
Isaac Chukwutem Abiodun,
Obiora E. Anisiji
Publication year - 2019
Publication title -
journal of energy research and reviews
Language(s) - English
Resource type - Journals
ISSN - 2581-8368
DOI - 10.9734/jenrr/2019/v2i330078
Subject(s) - statistics , distribution (mathematics) , meteorology , mean squared error , probability distribution , environmental science , mathematics , radiation , logistic regression , probability density function , geography , physics , mathematical analysis , quantum mechanics
This study has attempted to assess the performance of the most suitable statistical distribution function for modelling solar radiation over Yenagoa, Bayelsa State in Nigeria. The probability distribution functions are tested based on eleven years (2007-2017) solar radiation data obtained from National Aeronautics and Space Administration (NASA). Six probability distribution functions are tested to ascertain the most appropriate one based on four different statistical tools and fitting accuracy. The associated parameters of the most appropriate fitted probability distribution function are calculated and the trends in the characteristic of the solar radiation are deduced. The result shows that logistic distribution presents the most suitable probability distribution function for modelling solar radiation over the selected environment with RMSE of 1.500 KWh/m/day, MAE of 1.260 KWh/m 2 /day, MAPE of 22.000% and R 2 of 0.880.When compared with the other five distribution functions, the same trend could be seen although with different values of RMSE, MAE, MAPE and R. The estimated distribution location and scale parameters of the model vary with month and season. The overall result will be useful for predicting future solar radiation over the Review Article Abiodun and Anisiji; JENRR, 2(3): 1-8, 2019; Article no.JENRR.47820 2 studied environment. It will also be a good reference point for the design of large solar power projects in Yenagoa in particular and south southern Nigerian environments at large.

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