Topology error detection and robust state estimation using nonlinear least absolute value

Sangwoo Park, Reza Mohammadi-Ghazi, Javad Lavaei

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

6 Scopus citations


This paper proposes a new technique for robust state estimation in the presence of a small number of topological errors for power systems modeled by AC power flow equations. The developed method leverages the availability of a large volume of SCADA measurements and minimizes the \ell-{1} norm of nonconvex residuals augmented by a nonlinear, but convex, regularizer. Noting that a power network can be represented by a graph, we first study the properties of the solution obtained by the proposed estimator and argue that, under mild conditions, this solution identifies (small) subgraphs of the network that contain the topological errors in the model used for the state estimation problem. Then, we propose a method that can efficiently detect the topological errors by searching over the identified subgraphs. Furthermore, we develop a theoretical upper bound on the state estimation error to guarantee the accuracy of the proposed state estimation technique. The efficacy of the developed framework is demonstrated through numerical simulations on an IEEE benchmark system.

Original languageEnglish (US)
Title of host publication2019 American Control Conference, ACC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages8
ISBN (Electronic)9781538679265
StatePublished - Jul 2019
Externally publishedYes
Event2019 American Control Conference, ACC 2019 - Philadelphia, United States
Duration: Jul 10 2019Jul 12 2019

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619


Conference2019 American Control Conference, ACC 2019
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering


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