Skip to main navigation Skip to search Skip to main content

A Convex Method of Generalized State Estimation Using Circuit-Theoretic Node-Breaker Model

Research output: Contribution to journalArticlepeer-review

Abstract

An accurate and up-to-date topology is critical for situational awareness of a power grid; however, wrong switch statuses due to physical damage, communication error, or cyber-attack, can often result in topology errors. To maintain situation awareness under the possible topology errors and bad data, this article develops ckt-GSE, a circuit-theoretic generalized state estimation method using node-breaker (NB) model. Ckt-GSE is a convex and scalable model that jointly estimates AC state variables and network topology, with robustness against different data errors. The method first constructs an equivalent circuit representation of the AC power grid by developing and aggregating linear circuit models of SCADA meters, phasor measurement units(PMUs), and switching devices. Then based on this circuit, ckt-GSE defines a constrained optimization problem using weighted least absolute value (WLAV) objective to form a robust estimator. The problem is a Linear Programming (LP) problem whose solution includes accurate AC states and a sparse vector of noise terms to identify topology errors and bad data. This article is the first to explore a circuit-theoretic approach for an AC-network constrained GSE algorithm that is: 1) applicable to the real-world data setting, 2) convex without relaxation, scalable with our circuit-based solver; and 3) robust with the ability to identify and reject different data errors.

Original languageEnglish
Pages (from-to)4897-4910
Number of pages14
JournalIEEE Transactions on Power Systems
Volume39
Issue number3
DOIs
StatePublished - May 1 2024

Keywords

  • Generalized state estimation
  • least absolute value
  • node-breaker model
  • topology error
  • wrong status data

Fingerprint

Dive into the research topics of 'A Convex Method of Generalized State Estimation Using Circuit-Theoretic Node-Breaker Model'. Together they form a unique fingerprint.

Cite this