The Future of Renewable Energy: AI-Powered Optimization and Smart Grid Technologies

Abstract

Renewable energy sources such as solar and wind face challenges related to intermittency, grid stability, and energy storage. This paper investigates how AI and machine learning can optimize energy generation, distribution, and consumption in smart grids. We analyze AI-driven forecasting models, demand response strategies, and predictive maintenance techniques that enhance the efficiency of renewable energy systems. Case studies from global smart grid projects are presented, highlighting the potential of AI in accelerating the transition to a sustainable energy future.