Low-Resolution Fault Localization Using Phasor Measurement Units with Community Detection

Mahdi Jamei, Anna Scaglione, Sean Peisert

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

A significant portion of the literature on fault localization assumes (more or less explicitly) that there are sufficient reliable measurements to guarantee that the system is observable. While several heuristics exist to break the observability barrier, they mostly rely on recognizing spatio-temporal patterns, without giving insights on how the performance are tied with the system features and the sensor deployment. In this paper, we try to fill this gap and investigate the limitations and performance limits of fault localization using Phasor Measurement Units (PMUs), in the low measurements regime, i.e., when the system is unobservable with the measurements available. Our main contribution is to show how one can leverage the scarce measurements to localize different type of distribution line faults (three-phase, single-phase to ground,..) at the level of sub-graph, rather than with the resolution of a line. We show that the resolution we obtain is strongly tied with the graph clustering notion in network science.

Original languageEnglish (US)
Title of host publication2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538679548
DOIs
StatePublished - Dec 24 2018
Event2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2018 - Aalborg, Denmark
Duration: Oct 29 2018Oct 31 2018

Other

Other2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2018
CountryDenmark
CityAalborg
Period10/29/1810/31/18

    Fingerprint

Keywords

  • Community Detection
  • Fault Localization
  • PMU

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Energy Engineering and Power Technology

Cite this

Jamei, M., Scaglione, A., & Peisert, S. (2018). Low-Resolution Fault Localization Using Phasor Measurement Units with Community Detection. In 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2018 [8587461] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SmartGridComm.2018.8587461