Fault Diagnosis and Early Warning of Power Systems Based on Artificial Intelligence

Abstract

This study attempts to offer a broad picture of where artificial intelligence (AI) currently stands in power system applications, touching on its role in fault diagnosis and early warning, while also weighing the difficulties encountered and possible routes ahead. Through a systematic review and synthesis of the available literature, the paper surveys the existing landscape of AI adoption within power systems, covering, among other things, expert systems and neural network approaches. The findings suggest that AI has indeed improved both the efficiency of fault detection and the overall operational performance of modern power grids. However, certain concerns persist, including data equilibrium reliability and real-time coordination, which remain open for deeper investigation. In response, the paper puts forward several policy-oriented suggestions for upcoming research efforts, and reaffirms the significance and untapped potential of AI applications in the power domain.