Abstract
The integration of artificial intelligence (AI) into smart grids offers a powerful approach to optimizing energy distribution, enhancing efficiency, and supporting sustainable energy use. AI-driven systems can process vast amounts of real-time data from sensors, meters, and renewable energy sources, enabling grid operators to optimize energy flow, predict demand, and prevent outages. This article explores the role of AI in smart grid optimization, focusing on how machine learning algorithms, predictive analytics, and real-time decision-making are transforming energy systems. We also discuss the challenges and future opportunities of implementing AI technologies in smart grids to promote sustainability and reduce carbon footprints.
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