AI and Machine Learning for Sustainable Energy: Predictive Modelling, Optimization and Socioeconomic Impact In The USA

This research explores how Machine Learning and AI can be used to enhance energy efficiency, forecast energy consumption trends, and optimize energy systems in the USA. This research used datasets comprising household energy usage, electric vehicle adoption trends, and smart grid analytics obtained from public sources, databases, and IoT sensor devices. This study applies advanced machine learning techniques such as deep learning, regression models, and ensemble learning to improve forecasting accuracy aimed at achieving efficient resource allocation. Additionally, this study investigates fault prediction in New Energy Vehicles (NEVs) and its implications for grid stability and energy demand management. The…