Online semidefinite programming for power system state estimation

Seung Jun Kim, Gang Wang, Georgios B Giannakis

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

10 Scopus citations

Abstract

Power system state estimation (PSSE) constitutes a crucial prerequisite for reliable operation of the power grid. A key challenge for accurate PSSE is the inherent nonlinearity of SCADA measurements in the system states. Recent proposals for static PSSE tackle this issue by exploiting hidden convexity structure and solving a semidefinite programming (SDP) relaxation. In this work, an online PSSE algorithm based on SDP relaxation is proposed, which enjoys a similar convexity advantage, while capitalizing on past measurements as well for improved performance. An online convex optimization technique is adopted to derive an efficient algorithm with strong performance guarantees. Numerical tests verify the efficacy of the proposed approach.

Original languageEnglish (US)
Title of host publication2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6024-6027
Number of pages4
ISBN (Print)9781479928927
DOIs
StatePublished - Jan 1 2014
Event2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 - Florence, Italy
Duration: May 4 2014May 9 2014

Other

Other2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
CountryItaly
CityFlorence
Period5/4/145/9/14

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