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This comprehensive review paper provides a thorough examination of currentadvancements and research in the field of arc fault detection for electricaldistribution systems. The increasing demand for electricity, coupled with theincreasing utilization of renewable energy sources, has necessitated vigilancein safeguarding electrical distribution systems against arc faults. Such faultscould lead to catastrophic accidents, including fires, equipment damage, lossof human life, and other critical issues. To mitigate these risks, this reviewarticle focuses on the identification and early detection of arc faults, with aparticular emphasis on the vital role of artificial intelligence (AI) in thedetection and prediction of arc faults. The paper explores a wide range ofmethodologies for arc fault detection and highlights the superior performanceof AI-based methods in accurately identifying arc faults when compared to otherapproaches. A thorough evaluation of existing methodologies is conducted bycategorizing them into distinct groups, which provides a structured frameworkfor understanding the current state of arc fault detection techniques. Thiscategorization serves as a foundation for identifying the existing constraintsand future research avenues in the domain of arc fault detection for electricaldistribution systems. This review paper provides the state of the art in arcfault detection, aiming to enhance safety and reliability in electricaldistribution systems and guide future research efforts.

Advancements in Arc Fault Detection for Electrical Distribution Systems: A Comprehensive Review from Artificial Intelligence Perspective