An Interphase Short-Circuit Fault Location Method for Distribution Networks Considering Topological Flexibility

The location of faults in distribution networks represents a crucial line of defence, ensuring the safe and reliable operation of these networks. This paper puts forth a methodology for the location of short-circuit faults between phases within the context of a distribution network information physics system. Firstly, a distribution network topology identification model is constructed, and a switching function based on the characteristics of an interphase short-circuit fault current is constructed to form a physical layer interphase short-circuit preconceived fault set. Subsequently, methodologies for processing information perturbations, including distortion, delay, and failure, are proposed. Fault current information is then extracted to form an information layer fault current array. Ultimately, a similarity function is constructed to correlate the fault characteristics of the physical and information layers. This is achieved through the utilization of the variational bee colony algorithm, which is employed to address the aforementioned issue. The efficacy and suitability of the proposed methodology are assessed in the context of single-point and multi-point faults, dynamic topology alterations, and information perturbations in distribution networks. To this end, a real-world project in Hebei and the IEEE system are employed as illustrative examples. The methodology proposed in this paper can facilitate the rapid and precise location of phase-to-phase short-circuits in physical information systems of distribution networks, thereby enhancing the reliability of power supply in new intelligent distribution networks.

Authors

Institutions

Publication Details

Journal
Processes
Published
2025-03-07
DOI
https://doi.org/10.3390/pr13030782
Citations
1
Primary Topic
Power Systems Fault Detection
Type
article
Field-Weighted Citation Impact
1.21

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An Interphase Short-Circuit Fault Location Method for Distribution Networks Considering Topological Flexibility

Qifang Chen, Hua Xie, Tong Li, Kai Li et al.
1 citations
Processes
Power Systems Fault Detection
1.21
article

An Interphase Short-Circuit Fault Location Method for Distribution Networks Considering Topological Flexibility

Qifang Chen, Hua Xie, Tong Li, Kai Li, Zhe Liu, Chunhua Yang
article en
1 citations

Abstract

The location of faults in distribution networks represents a crucial line of defence, ensuring the safe and reliable operation of these networks. This paper puts forth a methodology for the location of short-circuit faults between phases within the context of a distribution network information physics system. Firstly, a distribution network topology identification model is constructed, and a switching function based on the characteristics of an interphase short-circuit fault current is constructed to form a physical layer interphase short-circuit preconceived fault set. Subsequently, methodologies for processing information perturbations, including distortion, delay, and failure, are proposed. Fault current information is then extracted to form an information layer fault current array. Ultimately, a similarity function is constructed to correlate the fault characteristics of the physical and information layers. This is achieved through the utilization of the variational bee colony algorithm, which is employed to address the aforementioned issue. The efficacy and suitability of the proposed methodology are assessed in the context of single-point and multi-point faults, dynamic topology alterations, and information perturbations in distribution networks. To this end, a real-world project in Hebei and the IEEE system are employed as illustrative examples. The methodology proposed in this paper can facilitate the rapid and precise location of phase-to-phase short-circuits in physical information systems of distribution networks, thereby enhancing the reliability of power supply in new intelligent distribution networks.

ProcessesVol. 13(3)
Beijing Jiaotong University (CN)
Ministry of Science and Technology of the People's Republic of China
Openalex Percentile: Top 24%
Power Systems Fault Detection
1.21
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.