Online Thevenin parameter tracking using synchrophasor data

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

There is significant interest in smart grid analytics based on phasor measurement data. One application is estimation of the Thevenin equivalent model of the grid from local measurements. In this paper, we propose methods using phasor measurement data to track Thevenin parameters at substations delivering power to both an unbalanced and balanced feeder. We show that for an unbalanced grid, it is possible to estimate the Thevenin parameters at each instant of time using only instantaneous phasor measurements. For balanced grids, we propose a method that is well-suited for online applications when the data is highly temporally-correlated over a short window of time. The effectiveness of the two methods is tested via simulation for two use-cases, one for monitoring voltage stability and the other for identifying cyber attackers performing 'reconnaissance' in a distribution substation.

Original languageEnglish (US)
Title of host publication2017 IEEE Power and Energy Society General Meeting, PESGM 2017
PublisherIEEE Computer Society
Pages1-5
Number of pages5
ISBN (Electronic)9781538622124
DOIs
StatePublished - Jan 29 2018
Event2017 IEEE Power and Energy Society General Meeting, PESGM 2017 - Chicago, United States
Duration: Jul 16 2017Jul 20 2017

Publication series

NameIEEE Power and Energy Society General Meeting
Volume2018-January
ISSN (Print)1944-9925
ISSN (Electronic)1944-9933

Other

Other2017 IEEE Power and Energy Society General Meeting, PESGM 2017
CountryUnited States
CityChicago
Period7/16/177/20/17

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Keywords

  • Anomaly Detection
  • Cybersecurity
  • Phasor Measurement Unit (PMU)
  • Thevenin Parameters

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Nuclear Energy and Engineering
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering

Cite this

Jamei, M., Scaglione, A., Roberts, C., McEachern, A., Stewart, E., Peisert, S., & McParland, C. (2018). Online Thevenin parameter tracking using synchrophasor data. In 2017 IEEE Power and Energy Society General Meeting, PESGM 2017 (pp. 1-5). (IEEE Power and Energy Society General Meeting; Vol. 2018-January). IEEE Computer Society. https://doi.org/10.1109/PESGM.2017.8273818