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

Conference · · 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2018
 [1];  [1];  [2]
  1. Arizona State Univ., Tempe, AZ (United States)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
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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.

Research Organization:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
DOE Contract Number:
AC02-05CH11231; OE0000780
OSTI ID:
1608264
Journal Information:
2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2018, Vol. 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

Figures / Tables (11)

Fig. 1(p. 3)figure Fig. 1
Fig. 2(p. 5)figure Fig. 2
Fig. 3(p. 5)figure Fig. 3
TABLE I(p. 5)table TABLE I
Fig. 4(p. 6)figure Fig. 4
Fig. 5(p. 6)figure Fig. 5
Fig. 6(p. 6)figure Fig. 6
Fig. 7(p. 6)figure Fig. 7
Figure 8(p. 7)figure Figure 8
TABLE II(p. 7)table TABLE II
TABLE III(p. 7)table TABLE III

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Related Subjects

Fault Localization
PMU
Community Detection