AI and Machine Learning in Electrical Systems

Abstract

ABSTRACT The integration of Artificial Intelligence (AI) and Machine Learning (ML) into electrical systems has been revolutionizing the way power generation, transmission, and distribution are managed. AI techniques, such as neural networks, fuzzy logic, and reinforcement learning, combined with ML models, enable intelligent monitoring, predictive maintenance, load forecasting, fault detection, and energy optimization. This paper reviews the current applications of AI and ML in electrical systems, highlighting their benefits, limitations, and future research directions. The review focuses on smart grids, renewable energy integration, predictive maintenance, and energy-efficient operations. Challenges such as data availability, computational requirements, and cyber-security concerns are discussed. The study concludes that AI and ML hold immense potential in improving system reliability, efficiency, and sustainability in electrical networks.

KEYWORDS:AI, Machine Learning, Electrical Systems, Smart Grids, Predictive Maintenance, Energy Optimization