Sustainable Energy Transition: Analyzing the Impact of Renewable Energy Sources on Global Power Generation

Abstract

This study delves into the intricate relationship between power plant attributes and electricity generation, employing data analysis and predictive modelling techniques. Through a comprehensive analysis of a global power plant dataset, critical factors such as plant capacity and commissioning year were identified as significant influencers on electricity generation. The research utilized correlation heatmaps to visually represent these relationships, offering valuable insights for policymakers and investors. A linear regression model was employed, leveraging capacity and commissioning year as features to predict electricity generation. The model's accuracy was evaluated using mean squared error, providing a quantitative measure of its predictive capabilities.