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

delete2026-01-31
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OA
AI
W
Wanxing Sheng
X
Xiaoyu Yang
D
Dongli Jia
K
Keyan Liu
Q
Qing Han *
C
Chengfeng Li
DOI:10.3390/pr14030493delete
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摘要

摘要

En 中文
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.
Keyword:
distributed generation
cluster partitioning
fault location
arithmetic optimization algorithm

期刊

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IF:
2.8
论文数:
7.5K
被引数:
3.7W

机构

S
shanghai university of electric power
学者数:
1.0K
论文数: 341
被引数: 0
C
China Electric Power Research Institute
学者数:
850
论文数: 437
被引数: 1.4K
引用论文

引用论文

A two-step state estimator with a suitable set of pseudo-measurements for precise fault location in distribution systems
err2024-11-01
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PREAI
errCavalcante, Paulo A. H.; Dardengo, Victor P.; Fernandes, Thiago R.; Cunha, Vinicius C.; Monaro, Renato M.; de Almeida, Madson C.
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