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.

Department(s)

Computer Science

Comments

National Science Foundation, Grant 1307458

Keywords and Phrases

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

International Standard Serial Number (ISSN)

2327-4662

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.

Publication Date

01 Dec 2016

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