This project explores the application of Generative AI techniques to modern power systems, specifically focusing on Non-Intrusive Load Monitoring (NILM) and synthetic data generation using time series data. NILM is instrumental in disaggregating total household energy consumption into appliance-specific patterns, allowing for a more detailed understanding of energy use without intrusive monitoring methods. This approach not only optimizes appliance usage but also enhances safety by identifying potential issues in electrical devices. This research supports the transition to clean energy solutions and contributes to a sustainable future by reducing environmental impact.