Partitioned fault location of distribution network with distributed generation based on improved binary dragonfly algorithm

Yi Wu; En Bo; Yi Zhang

doi:10.1117/12.2679757

18 July 2023 Partitioned fault location of distribution network with distributed generation based on improved binary dragonfly algorithm

Yi Wu, En Bo, Yi Zhang

Author Affiliations +

Proceedings Volume 12722, Third International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2023); 1272221 (2023) https://doi.org/10.1117/12.2679757
Event: International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2023), 2023, Hangzhou, China

Abstract

A zonal fault location model based on the improved binary dragonfly algorithm is proposed to solve the problem of fast and fault-tolerant fault location in multi-branch distribution networks containing distributed power sources. Firstly, a chaotic mapping strategy is introduced in the initialization stage of the algorithm population to improve the initial population's quality. The linear inertia weights of the original dragonfly algorithm are nonlinearly enhanced to improve the convergence speed of the algorithm. The equivalent partitioning model of distribution networks with distributed power sources is established based on the "black box method," and a location correction mechanism is added to guarantee location accuracy. Finally, the simulation is verified in a multi-branch distribution network with distributed power supply. Compared with the traditional binary dragonfly algorithm partitioning model, the number of iterations of localization is reduced. In addition, the improved binary dragonfly partitioning model can quickly and accurately locate the fault section for different fault locations and aberration points.

Citation Download Citation

Yi Wu, En Bo, and Yi Zhang "Partitioned fault location of distribution network with distributed generation based on improved binary dragonfly algorithm", Proc. SPIE 12722, Third International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2023), 1272221 (18 July 2023); https://doi.org/10.1117/12.2679757

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