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

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. Here, we show that the resolution we obtain is strongly tied with the graph clustering notion in network science.

Authors:
 [1];  [1];  [2]
  1. Arizona State Univ., Tempe, AZ (United States)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1608264
DOE Contract Number:  
AC02-05CH11231; OE0000780
Resource Type:
Conference
Journal Name:
2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2018
Additional Journal Information:
Journal Volume: 2018; Conference: 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), Aalborg (Denmark), 29-31 Oct 2018
Country of Publication:
United States
Language:
English
Subject:
Fault Localization; PMU; Community Detection

Citation Formats

Jamei, Mahdi, Scaglione, Anna, and Peisert, Sean. Low-Resolution Fault Localization Using Phasor Measurement Units with Community Detection. United States: N. p., 2018. Web. doi:10.1109/SmartGridComm.2018.8587461.
Jamei, Mahdi, Scaglione, Anna, & Peisert, Sean. Low-Resolution Fault Localization Using Phasor Measurement Units with Community Detection. United States. https://doi.org/10.1109/SmartGridComm.2018.8587461
Jamei, Mahdi, Scaglione, Anna, and Peisert, Sean. 2018. "Low-Resolution Fault Localization Using Phasor Measurement Units with Community Detection". United States. https://doi.org/10.1109/SmartGridComm.2018.8587461. https://www.osti.gov/servlets/purl/1608264.
@article{osti_1608264,
title = {Low-Resolution Fault Localization Using Phasor Measurement Units with Community Detection},
author = {Jamei, Mahdi and Scaglione, Anna and Peisert, Sean},
abstractNote = {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. Here, we show that the resolution we obtain is strongly tied with the graph clustering notion in network science.},
doi = {10.1109/SmartGridComm.2018.8587461},
url = {https://www.osti.gov/biblio/1608264}, journal = {2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2018},
number = ,
volume = 2018,
place = {United States},
year = {2018},
month = {10}
}

Conference:
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