Publication detail

Fault Detection in Mesh Network Utilizing Measured Data from MV/LV Transformer Stations

KRČÁL, V. TOPOLÁNEK, D.

Original Title

Fault Detection in Mesh Network Utilizing Measured Data from MV/LV Transformer Stations

Type

conference paper

Language

English

Original Abstract

This paper aims at fault detection in a low voltage meshed network based on current monitoring at distribution transformer stations. For indication of fuse (or line) interruption a simple algorithm has been designed. The algorithm is based on evaluating current changes at low voltage feeders and comparing them to threshold values derived from normal operation state. For correct setting of threshold values of current changes, sensitivity analysis of load behavior is carried out. The network sensitivity to load changes is presented using both normalized load profile data and real measured data from several distribution stations. The algorithm performance is then tested on a numerical model considering interruption of each individual line section (fuse breaking). The simulations are carried out with a number of different threshold settings using extensive meshed network model. The study is supplemented with topological categorization of line sections to specify the position of the interrupted line within the network.

Keywords

meshed network; distributed measurement; fault detection; current changes; low voltage

Authors

KRČÁL, V.; TOPOLÁNEK, D.

Released

12. 9. 2022

Publisher

Technical University of Košice

Location

Košice

ISBN

978-80-553-4104-0

Book

Proceedings of the 11th International Scientific Symposium on Electrical Power Engineering ELEKTROENERGETIKA 2022

Edition

1

Pages from

272

Pages to

276

Pages count

5

BibTex

@inproceedings{BUT178499,
  author="Vít {Krčál} and David {Topolánek}",
  title="Fault Detection in Mesh Network Utilizing Measured Data from MV/LV Transformer Stations",
  booktitle="Proceedings of the 11th International Scientific Symposium on Electrical Power Engineering
ELEKTROENERGETIKA 2022",
  year="2022",
  series="1",
  pages="272--276",
  publisher="Technical University of Košice",
  address="Košice",
  isbn="978-80-553-4104-0"
}