Application of Artificial Intelligence in Electrical System Monitoring and Control

Abstract

Artificial Intelligence (AI) has emerged as a transformative force in the domain of electrical engineering, particularly in system monitoring, fault detection, and predictive maintenance. This paper presents an extensive overview of AI-based applications in electrical systems, focusing on machine learning (ML) algorithms, neural networks, and deep learning techniques. By processing vast amounts of operational data from sensors and grid components, AI systems can detect anomalies, predict equipment failures, and optimize load management. The study examines various use cases, such as condition monitoring of transformers, predictive analysis for power system stability, and automated fault diagnosis in power distribution networks. Moreover, the paper discusses the integration of AI with Internet of Things (IoT) devices, cloud computing, and edge computing paradigms, enabling real-time, decentralized decision-making capabilities.

KEYWORDS: Artificial Intelligence, Predictive Maintenance, Machine Learning, IoT Integration, System Monitoring