Exponentially Fast Estimation of Power System Oscillation Modes Using Distributed Phasor Data

Ji Liu, Aranya Chakrabortty, Tamer Basar

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

Abstract

We address the problem of distributed estimation of eigenvalues in power system models using synchronized phasor measurements. The power system is partitioned into a set of non-overlapping areas, each of which is equipped with a local estimator. Online measurements of bus voltage and current phasors from a limited number of buses in each area are used for identifying the characteristic polynomial of the system in a distributed fashion by exchanging information between these local estimators and a central estimator. We develop a new variant of distributed least squares for carrying out this estimation, and show that the algorithm converges with exponential speed. The identified characteristic polynomial is finally used for estimating the eigenvalues. Both synchronous and asynchronous versions of the algorithm are proposed. The algorithm can be implemented without any matrix inversion with minor modification. Results are validated using the IEEE 68-bus power system model with five areas.

Original languageEnglish (US)
Title of host publication2019 IEEE 58th Conference on Decision and Control, CDC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7506-7511
Number of pages6
ISBN (Electronic)9781728113982
DOIs
StatePublished - Dec 2019
Event58th IEEE Conference on Decision and Control, CDC 2019 - Nice, France
Duration: Dec 11 2019Dec 13 2019

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume2019-December
ISSN (Print)0743-1546

Conference

Conference58th IEEE Conference on Decision and Control, CDC 2019
CountryFrance
CityNice
Period12/11/1912/13/19

Keywords

  • cyber-physical systems
  • Distributed estimation
  • oscillation monitoring
  • power systems

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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