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 journalArticle

12 Citations (Scopus)

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 Micro-Phasor 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, a source-constrained optimal μPMU placement 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)
JournalIEEE Transactions on Power Systems
DOIs
StateAccepted/In press - Oct 24 2017
Externally publishedYes

Fingerprint

Phasor measurement units
Sensors
Fusion reactions
Monitoring

Keywords

  • Anomaly detection
  • Anomaly Detection
  • Distribution Grid
  • Manganese
  • Mathematical model
  • Micro-Phasor Measurement Unit (PMU)
  • Optimal Placement
  • Phasor measurement units
  • Real-time systems
  • Sensors
  • Steady-state

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

Cite this

Anomaly Detection Using Optimally-Placed μPMU Sensors in Distribution Grids. / Jamei, Mahdi; Scaglione, Anna; Roberts, Ciaran; Stewart, Emma; Peisert, Sean; McParland, Chuck; McEachern, Alex.

In: IEEE Transactions on Power Systems, 24.10.2017.

Research output: Contribution to journalArticle

Jamei, Mahdi ; Scaglione, Anna ; Roberts, Ciaran ; Stewart, Emma ; Peisert, Sean ; McParland, Chuck ; McEachern, Alex. / Anomaly Detection Using Optimally-Placed μPMU Sensors in Distribution Grids. In: IEEE Transactions on Power Systems. 2017.
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