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
- Yongtao Tian (ORCID: https://orcid.org/0000-0001-5011-6878)
- Zhihua Zhang (ORCID: https://orcid.org/0000-0003-1427-1074)
- Yongliang Liang (ORCID: https://orcid.org/0000-0002-3773-7298)
- Yuxiao Xing
- Bingyin Xu (ORCID: https://orcid.org/0000-0003-4084-7137)
- Hongjie Wu
- Duhao Song
Institutions
- Shandong University of Technology (CN)
- Shandong University (CN)
- State Grid Corporation of China (China) (CN)
- China University of Petroleum, East China (CN)
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
- National Natural Science Foundation of China
- Natural Science Foundation of Shandong Province
- Fundamental Research Funds for the Central Universities