Anomaly detection using optimally placed μPMU sensors in distribution grids

Mahdi Jamei, Anna Scaglione, Ciaran Roberts, Emma Stewart, Sean Peisert, Chuck McParland, Alex McEachern

Research output: Contribution to journalArticlepeer-review

49 Scopus citations

Abstract

As the distribution grid moves toward a tightly monitored network, it is important to automate the analysis of the enormous amount of data produced by the sensors to increase the operators situational awareness about the system. In this paper, focusing on microphasor measurement unit (μPMU) data, we propose a hierarchical architecture for monitoring the grid and establish a set of analytics and sensor fusion primitives for the detection of abnormal behavior in the control perimeter. Due to the key role of the μPMU devices in our architecture, an optimal μPMU placement with limited number of sensors is also described that finds the best location of the devices with respect to our rules. The effectiveness of the proposed methods are tested through the synthetic and real μPMU data.

Original languageEnglish (US)
Pages (from-to)3611-3623
Number of pages13
JournalIEEE Transactions on Power Systems
Volume33
Issue number4
DOIs
StatePublished - Jul 2018
Externally publishedYes

Keywords

  • Distribution grid
  • anomaly detection
  • micro-phasor measurement unit (μPMU)
  • optimal placement

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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