Fault Detection and Fault Diagnosis in Power System Using AI: A Review

Abstract

Electricity, which is essential to modern society, necessitates a consistent and uninterrupted supply. Faults in power systems pose difficulties, highlighting the vital importance of fault identification and diagnosis. This review paper provides a concise overview of artificial intelligence-based fault detection and diagnosis in power systems. The primary focus is on deep learning; on the one hand, it compares various works and acts as a primer for those who are unfamiliar with them. On the other hand, it delves into the application of UV-visible video processing to detect incipient faults by analyzing corona discharge and air ionization. Moreover, this state-of-the-art work highlights deep learning applications, particularly in UV-visible video processing, with the goal of detecting incipient faults through corona discharge and air ionization analysis. Despite ongoing research, the field lacks a clear path and structure, emphasizing the need for continued advancement in utilizing AI for effective fault detection and diagnosis in power systems.