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International Journal of Robust and Nonlinear Control
Article . 2021 . Peer-reviewed
License: Wiley Online Library User Agreement
Data sources: Crossref
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
zbMATH Open
Article . 2022
Data sources: zbMATH Open
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Distributed fault detection and isolation for power system

Authors: Limei Liang; Shuai Liu; Yueyang Li; Maiying Zhong; Yueying Li;

Distributed fault detection and isolation for power system

Abstract

AbstractIn this article, a novel distributed fault detection and isolation method is proposed for large‐scale power system affected by additive type of faults and energy bounded disturbances. First, in order to design the local residual generators, a bank of Luenberger observers are designed to estimate the local states of the system, and the parameters of each local residual generator are determined by solving the corresponding optimization problem, which guarantees that the residual generator is sensitive to faults while robust to energy bounded disturbances. When the local residual exceeds the corresponding threshold, the occurrence of a fault in each agent is recognized. Then, for the case that power system with both process noises and measurement noises, the specific fault detection thresholds are designed with the aid of the Chebyshev inequality. Finally, the effectiveness of the proposed scheme is validated via illustrative example.

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Keywords

power system, residual generator, Large-scale systems, fault detection and isolation, time-varying threshold, Networked control, \(H^\infty\)-control, Observers

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Top 10%
Top 10%
Top 10%
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