Introduces a revolutionary approach that combines time series analysis with cutting-edge machine learning techniques to optimize the use of renewable energy sources. The proposed approach focuses on accurately forecasting energy generation from renewable sources such as solar and wind power using data-driven predictive modeling. The primary objective is to provide energy sector stakeholders with actionable insights to effectively anticipate variations in renewable energy generation by developing and deploying advanced prediction models. As part of the proposed solution, a dynamic dashboard is implemented to provide real-time visibility into machinery’s utilization of renewable energy. Additionally, the dashboard incorporates sophisticated threshold alerts to promptly notify relevant stakeholders when energy consumption exceeds predefined criteria. This proactive approach enables stakeholders to make informed decisions and optimize resource utilization efficiently.