State and noise covariance estimation in power grids using limited nodal PMUs

Deepjyoti Deka, Armin Zare, Andrey Lokhov, Mihailo Jovanovic, Michael Chertkov

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

3 Scopus citations

Abstract

The statistics of critical state variables and nodal fluctuations in power grids are useful for control of its dynamics and procurement of regulation resources. This paper studies estimation of the statistics of grid state variables and ambient fluctuations using time-stamped nodal measurements collected from limited PMUs in the grid. We show that in the presence of time-stamped observations that enable computation of delayed covariances, PMUs located at half of the number of grid buses are sufficient to reconstruct all state and noise statistics exactly. For lower number of available PMUs, we provide a convex optimization framework for estimating the covariance matrices that outshines standard schemes that do not utilize the availability of time-stamped measurements.

Original languageEnglish (US)
Title of host publication2017 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1075-1079
Number of pages5
ISBN (Electronic)9781509059904
DOIs
StatePublished - Mar 7 2018
Externally publishedYes
Event5th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 - Montreal, Canada
Duration: Nov 14 2017Nov 16 2017

Publication series

Name2017 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 - Proceedings
Volume2018-January

Conference

Conference5th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017
Country/TerritoryCanada
CityMontreal
Period11/14/1711/16/17

Keywords

  • Covariance completion
  • Delayed covariance
  • Lyapunov equation
  • PMU
  • Power grid
  • Swing dynamics

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing

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