Data-Driven Topology Estimation with Limited Sensors in Radial Distribution Feeders

被引:4
|
作者
Bariya, Mohini [1 ]
von Meier, Alexandra [1 ]
Ostfeld, Aminy [1 ]
Ratnam, Elizabeth [1 ]
机构
[1] Univ Calif Berkeley, Dept Elect Engn, Berkeley, CA 94720 USA
来源
2018 IEEE GREEN TECHNOLOGIES CONFERENCE (GREENTECH) | 2018年
关键词
D O I
10.1109/GreenTech.2018.00041
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Topology estimation is a central part of the wider state estimation problem in electrical networks. We describe a method for data-driven topology estimation in radial distribution feeders with limited sensors. Our algorithm, based on voltage event correlation, estimates a fixed, unknown topology using voltage magnitude measurements collected over several hours and stored in the high performance time-series Berkeley Tree Database. In addition to a topology estimate, our correlation-based algorithm returns a short, human-interpretable snapshot of measurement data that validates the topology estimate. We test our correlation based algorithm on microsynchrophasor (mu PMU) data collected on an operational distribution feeder.
引用
收藏
页码:183 / 188
页数:6
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