This article reviews the use of deep learning methods for short-circuit fault detection, classification, and localization in power distribution systems, including symmetrical, asymmetrical, and high-impedance faults. The review is organized into several sections that cover different aspects of the methods proposed. The incorporation of generation at demand points produces a variety of load flow and fault currents, changing.
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