AI-Powered Smart Grids: Security Challenges and Intelligent Energy Management Approaches

Abstract

Electric power systems are being transformed into smart grids that can operate with flexibility, efficiency, and resilience thanks to the confluence of enhanced sensing, communication, distributed energy resources, and artificial intelligence. With an emphasis on security issues and clever energy management strategies, this study examines the current status of AI-powered smart grids. We present an architectural overview, pinpoint attack surfaces and threat models, and look at particular security risks such as supply-chain vulnerabilities, data integrity assaults, and privacy violations. Next, we examine AI-driven methods for distributed generation coordination, demand response, energy forecasting, and real-time optimization, and we talk about how these methods relate to privacy and security issues. We then assess defense methods such as blockchain-enabled coordination, privacy-preserving analytics, federated learning, anomaly detection, and secure communication protocols. We offer case examples and a thorough design pattern that strikes a compromise between privacy, robustness, and performance. A research agenda for safe, intelligent, and reliable smart grids, as well as suggestions for practitioners, is included in the paper's conclusion.