Centric Data Analytics Framework for Solar Energy Efficiency in the Rural Settings

Abstract

Climate change periodically, and one of its natural causes is solar variation. Solar energy generation is now gaining more attention in developed nations, and its usefulness is becoming acceptable in rural settings. This research focused on Centric Data Analytics Framework for Solar Energy Efficiency called DAFSEE to solve power supply deficiency in resource-limited settings in Kwara State. Statistically, resource-limited regions feature a low population with a shortfall of social amenities. Significantly, households in urban areas have more electricity consumption than rural ones, making solar energy more relevant. The researcher then determined the efficiency of solar energy in the selected regions over time using an experimental study using cloud computing to create a dataset in six geo-locations in Kwara State. A predictive model was adopted and yielded 98.99% from the recurring analytics of the installed solar cells. The outcome of this study suggested best practices to sustain renewable energy in the area across all seasons. The study provides a starting point to distil policy implications for a centric analytics framework of improving rural electrification relevant for collective resource-limited settings across Nigeria.