Voltage mapping model based short-circuit fault location method in distribution network with DG

• Data dimensionality enhancement is achieved through inversion calculation. • Only magnitude information of the phase-to-phase voltage is required. • Precise fault distance measurement within the fault section is achieved. • Ensure accurate fault location under various influencing factors. With the rapid development of smart grid, low-voltage detection data is becoming increasingly abundant. However, the data utilization is not deep enough. In this paper, a method for fault location of medium-voltage side based on low-voltage monitoring information is proposed. Firstly, the mapping model of low-voltage side phase-to-phase voltage amplitude and medium-voltage side voltage phasor is deduced, when short-circuit fault occurs. Then, according to the distribution characteristics of voltage and current phasor information calculated on the medium-voltage side, short-circuit fault section location and fault distance measurement method is presented separately. Meanwhile, the implementation process for the fault location method is given and the influence factor is analyzed. Finally, IEEE 33 nodes distribution network simulation model is constructed by PSCAD/EMTDC. The simulation results verify the accuracy of the voltage mapping model and the effectiveness of the location method. It provides a new approach for the in-depth utilization of low-voltage monitoring information.

Authors

Institutions

Publication Details

Journal
International Journal of Electrical Power & Energy Systems
Published
2025-05-22
DOI
https://doi.org/10.1016/j.ijepes.2025.110767
Citations
2
Primary Topic
Power Systems Fault Detection
Type
article
Field-Weighted Citation Impact
2.43

Funders

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

Voltage mapping model based short-circuit fault location method in distribution network with DG

Yongtao Tian, Zhihua Zhang, Yongliang Liang, Yuxiao Xing et al.
2 citations
International Journal of Electrical Power & Energy Systems
Power Systems Fault Detection
2.43
article

Voltage mapping model based short-circuit fault location method in distribution network with DG

Yongtao Tian, Zhihua Zhang, Yongliang Liang, Yuxiao Xing, Bingyin Xu, Hongjie Wu, Duhao Song
article en
2 citations

Abstract

• Data dimensionality enhancement is achieved through inversion calculation. • Only magnitude information of the phase-to-phase voltage is required. • Precise fault distance measurement within the fault section is achieved. • Ensure accurate fault location under various influencing factors. With the rapid development of smart grid, low-voltage detection data is becoming increasingly abundant. However, the data utilization is not deep enough. In this paper, a method for fault location of medium-voltage side based on low-voltage monitoring information is proposed. Firstly, the mapping model of low-voltage side phase-to-phase voltage amplitude and medium-voltage side voltage phasor is deduced, when short-circuit fault occurs. Then, according to the distribution characteristics of voltage and current phasor information calculated on the medium-voltage side, short-circuit fault section location and fault distance measurement method is presented separately. Meanwhile, the implementation process for the fault location method is given and the influence factor is analyzed. Finally, IEEE 33 nodes distribution network simulation model is constructed by PSCAD/EMTDC. The simulation results verify the accuracy of the voltage mapping model and the effectiveness of the location method. It provides a new approach for the in-depth utilization of low-voltage monitoring information.

International Journal of Electrical Power & Energy SystemsVol. 169
Shandong University of Technology (CN), Shandong University (CN), State Grid Corporation of China (China) (CN), China University of Petroleum, East China (CN)
National Natural Science Foundation of China, Natural Science Foundation of Shandong Province, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 11%
Power Systems Fault Detection
2.43
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.