Fast modal identification, monitoring, and visualization for large-scale power systems using Dynamic Mode Decomposition

Saurav Mohapatra, Thomas J. Overbye

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

Abstract

Dynamic Mode Decomposition (DMD) is a relatively new method for simultaneous modal analysis of multiple time-series signals. In this paper, DMD is successfully applied towards transmission-level power system data in an implementation that is able to run quickly. Since power systems are considered as non-linear and time-varying, modal identification is capable of monitoring the evolution of large-scale power system dynamics by providing a breakdown of the constituent oscillation frequencies and damping ratios, and their respective amplitudes. DMD is an efficient algorithm for both off-line and on-line processing of large volumes of time-series measurements, which can enable spatio-temporal analyses, improve situational awareness, and could even contribute towards control strategies. This paper applies DMD on a set of simulated measurements consisting of both frequency and voltage magnitude data. The key advantage of this implementation is its relatively fast computation; for example, it is able to process a 7 s time-window, consisting of 3392 signals with 211 time points, in 0.185 s. Automated processing of transient contingency results, and on-line mode tracking are two proposed applications.

Original languageEnglish (US)
Title of host publication19th Power Systems Computation Conference, PSCC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9788894105124
DOIs
StatePublished - Aug 10 2016
Event19th Power Systems Computation Conference, PSCC 2016 - Genova, Italy
Duration: Jun 20 2016Jun 24 2016

Publication series

Name19th Power Systems Computation Conference, PSCC 2016

Other

Other19th Power Systems Computation Conference, PSCC 2016
Country/TerritoryItaly
CityGenova
Period6/20/166/24/16

Keywords

  • Modal identification
  • and visualization
  • power system dynamics
  • situational awareness
  • transient stability

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Energy Engineering and Power Technology

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