AI based Fault Detection Method & Challenges in Power Distribution Networks

Abstract

Fault detection in power distribution networks is critical for ensuring system reliability, minimizing downtime, and reducing economic losses. Traditional methods, while effective in simple grid configurations, struggle to address the complexities of modern, decentralized, and data-intensive power systems. This research investigates the application of artificial intelligence (AI) techniques to enhance fault detection in power distribution networks. By leveraging machine learning (ML), deep learning (DL), and advanced AI
paradigms, this study aims to develop robust solutions capable of detecting and classifying faults with higher accuracy and speed. This review paper focused on AI based Fault Detection Method & Challenges in Power Distribution Networks. The findings contribute to the
growing body of knowledge in the field, providing actionable insights for academia and industry stakeholder.