Zobrazit v EDS

Fault Location Method for Distribution Networks Based on Cluster Partitioning and Arithmetic Optimization Algorithm

Uloženo v:
Podrobná bibliografie
Název: Fault Location Method for Distribution Networks Based on Cluster Partitioning and Arithmetic Optimization Algorithm
Autoři: Wanxing Sheng, Xiaoyu Yang, Dongli Jia, Keyan Liu, Qing Han, Chengfeng Li
Zdroj: Processes ; Volume 14 ; Issue 3 ; Pages: 493
Informace o vydavateli: Multidisciplinary Digital Publishing Institute
Rok vydání: 2026
Sbírka: MDPI Open Access Publishing
Témata: distributed generation, cluster partitioning, fault location, arithmetic optimization algorithm
Geografické téma: agris
Popis: The large-scale integration of Distributed Generators (DGs) has significantly altered fault characteristics in distribution networks, posing challenges to conventional fault location methods. To address these limitations, this paper presents a novel approach that combines dynamic cluster partitioning with the arithmetic optimization algorithm (AOA). The proposed method first divides the network into autonomous clusters based on electrical coupling, facilitating preliminary fault area identification. Subsequently, the AOA optimizes fault section identification through current matching analysis. Using MATLAB simulations on an IEEE 33-node system with various DG types and fault scenarios, the method demonstrates superior accuracy and faster convergence compared to traditional approaches. Results confirm its effectiveness in improving fault location performance for modern distribution networks with high DG penetration.
Druh dokumentu: text
Popis souboru: application/pdf
Jazyk: English
Relation: Energy Systems; https://dx.doi.org/10.3390/pr14030493
DOI: 10.3390/pr14030493
Dostupnost: https://doi.org/10.3390/pr14030493
Rights: https://creativecommons.org/licenses/by/4.0/
Přístupové číslo: edsbas.10CB5ECD
Databáze: BASE
Popis
Abstrakt:The large-scale integration of Distributed Generators (DGs) has significantly altered fault characteristics in distribution networks, posing challenges to conventional fault location methods. To address these limitations, this paper presents a novel approach that combines dynamic cluster partitioning with the arithmetic optimization algorithm (AOA). The proposed method first divides the network into autonomous clusters based on electrical coupling, facilitating preliminary fault area identification. Subsequently, the AOA optimizes fault section identification through current matching analysis. Using MATLAB simulations on an IEEE 33-node system with various DG types and fault scenarios, the method demonstrates superior accuracy and faster convergence compared to traditional approaches. Results confirm its effectiveness in improving fault location performance for modern distribution networks with high DG penetration.
DOI:10.3390/pr14030493