A distribution network fault location model based on multi source information and genetic algorithm

Yongzhi Yang; Qiuhong Xie

doi:10.1117/12.3011654

7 December 2023 A distribution network fault location model based on multi source information and genetic algorithm

Yongzhi Yang, Qiuhong Xie

Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 129410Y (2023) https://doi.org/10.1117/12.3011654
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China

Abstract

This study aims to enhance fault localization in distribution networks to ensure reliable electricity supply. Two fault location methods, range location, and section location, have been analyzed. The section location method, known for its fault tolerance, has been the focus of investigation. The Matrix algorithm and intelligent optimization algorithms have been explored to improve fault location accuracy. Three key contributions have been proposed: establishing a correlation model between low-voltage customer power outage data and fault section variables, developing a robust fault location model based on functional relationships, and conducting simulation experiments to demonstrate enhanced accuracy and robustness. The research outcomes provide practical insights into enhancing power system reliability.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yongzhi Yang and Qiuhong Xie "A distribution network fault location model based on multi source information and genetic algorithm", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 129410Y (7 December 2023); https://doi.org/10.1117/12.3011654

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