Uncovering Power Transmission Dynamic Model from Incomplete PMU Observations

Andrey Y. Lokhov, Deepjyoti Deka, Marc Vuffray, Michael Chertkov

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Proliferation of Phasor Measurement Units (PMUs) that allow for a synchronous and distributed collection of data can be leveraged to obtain reliable information about the power system model. In practice, one has to account for the system being partially observed as not every bus hosts a PMU. We consider the problem of partial recovery of the underlying dynamic state matrix of transmission power grids from time-stamped PMU measurements on a subset of nodes in a network. We propose a data-driven method which does not assume any knowledge of system parameters and only relies on basic assumptions about the system dynamics. The method is based on a least-squares regression with a nuclear norm regularization that accounts for the effect of hidden observations, supplemented with structural physics-informed constraints that enforce the identifiability. Performance of the method is demonstrated on an IEEE test case example.

Original languageEnglish
Title of host publication2018 IEEE Conference on Decision and Control, CDC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4008-4013
Number of pages6
ISBN (Electronic)9781538613955
DOIs
Publication statusPublished - 18 Jan 2019
Externally publishedYes
Event57th IEEE Conference on Decision and Control, CDC 2018 - Miami, United States
Duration: 17 Dec 201819 Dec 2018

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume2018-December
ISSN (Print)0743-1546

Conference

Conference57th IEEE Conference on Decision and Control, CDC 2018
Country/TerritoryUnited States
CityMiami
Period17/12/1819/12/18

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