ADVANCES IN AI-POWERED GRID MANAGEMENT: TOWARD AUTONOMOUS ENERGY SYSTEMS

Abstract

This article explores the revolutionary impact of artificial intelligence (AI) on power grid management, focusing on developing autonomous and intelligent control systems. It reviews recent advancements in AI-powered grid technologies, including predictive maintenance, real-time demand balancing, and autonomous power restoration. The article examines how AI-driven models process vast amounts of data from various sources to predict and prevent grid failures, significantly reducing operational costs and minimizing outages. It also highlights breakthroughs in demand response systems that optimize electricity distribution through dynamic supply adjustments based on real-time consumption patterns. The article presents case studies from global pilot programs demonstrating successful implementations of AI-powered grid systems, showcasing reductions in energy waste and improvements in power reliability and efficiency. Looking to the future, the article discusses emerging innovations such as AI-based swarm intelligence algorithms and self-healing grids, which promise to minimize human intervention in grid management. The article concludes by addressing the policy implications and regulatory challenges associated with integrating AI into energy infrastructure, emphasizing the need to balance innovation with security and reliability concerns. Throughout, the article underscores the potential of AI-powered smart grids to address climate change, meet growing energy demands, and ensure long-term energy security and sustainability.