OPTIMIZING SOLAR POWER GENERATION IN NIGERIA:REGRESSION ANALYSIS OF SOLAR RADIATION AND CLIMATIC VARIABLES FOR ENHANCED ENERGY FORECASTING
Abstract
The growing demand for sustainable and reliable energy in Nigeria has highlighted the need to harness solar power as a viable alternative to fossil fuels. Despite Nigeria’s abundant solar radiation, effective utilization of solar energy is often hindered by fluctuations caused by climatic variations. This study focuses on optimizing solar power generation through regression analysis of solar radiation and selected climatic variables, with particular emphasis on temperature and wind speed in Ikeja, Lagos. Multiple Linear Regression (MLR) was employed to establish a predictive model quantifying the relationship between solar radiation (dependent variable) and the independent variables. The findings reveal significant correlations, providing a statistical framework for forecasting solar energy output under varying climatic conditions. The developed model not only enhances the accuracy of energy forecasting but also supports informed decision-making in solar power system planning and deployment. Ultimately, this research contributes to advancing renewable energy strategies and promoting sustainable energy development in Nigeria.
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