A Hypothesis Testing Approach for Topology Error Detection in Power Grids

Wei Biao Wu, Maggie X. Cheng, Bei Gou

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

When the grid topology is changed due to incidents and the state estimator is not updated with the topological change, it is considered a topology error. In this paper, we develop a new method for detecting topology errors in power grids. The proposed method considers the measurement data as a nonstationary Gaussian process, explores the dependence structure of the underlying process. It detects errors by testing the hypothesis of whether the mean vector of a nonstationary Gaussian process is zero and does not rely on the convergence of the standard weighted least-squares (WLS) state estimation algorithm. It is very effective in detecting topology errors, in which multiple conforming errors may occur and the traditional state estimation algorithms may fail to converge. Simulation results show that it can accurately identify the abnormal measurements caused by the topology error.

Original languageEnglish (US)
Article number7428828
Pages (from-to)979-985
Number of pages7
JournalIEEE Internet of Things Journal
Volume3
Issue number6
DOIs
StatePublished - Dec 2016

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications

Keywords

  • Anomaly detection
  • Gaussian process
  • hypothesis testing
  • power grid
  • state estimation
  • topology error

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