Fault Section Localization in Distribution Networks Based on the Integration of Node Classification Matrix and an Improved Binary Particle Swarm Algorithm

Single-phase-to-ground faults occur frequently in distribution networks, and traditional localization methods have limitations such as insufficient feature extraction and poor topological adaptability. This paper proposes a two-stage localization method integrating the node classification matrix and the improved binary particle swarm optimization (IBPSO) algorithm: the node classification matrix achieves rapid initial localization, while IBPSO performs error correction. Simulation verification based on the IEEE 33-bus model shows that the method achieves a localization accuracy of 96%, which is 19% higher than that of the node classification matrix and 2% higher than that of IBPSO. It still maintains an accuracy of over 95% under scenarios of 1-3 node distortions, topological switching, and 5000Ω high-impedance faults, and is compatible with existing FTU (Feeder Terminal Unit) devices. This method effectively balances localization speed and robustness, providing a reliable solution for the rapid isolation of distribution network faults.