This research project focuses on optimizing renewable energy systems using Big Data Analytics. The study analyses massive datasets generated from solar, wind, and smart grid sources to improve energy forecasting, demand prediction, and efficiency. Using data mining, machine learning models, and distributed processing frameworks like Hadoop and Spark, the system identifies patterns that enhance energy generation and reduce wastage. The project provides a scalable architecture for handling high-volume energy data and demonstrates how analytics-driven insights support sustainability and reliable energy distribution.