Information Correction-Based Analytical Model for Fault Section Diagnosis of Power Systems

The diagnostic accuracy of analytical models for fault section diagnosis of power systems relies heavily on the correction of protective relays (PRs) and circuit breakers (CBs). The current analytical models use the received alarm information directly, but the actions of PRs and CBs are fraught with...

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Bibliographic Details
Published in:IEEE transactions on reliability Vol. 74; no. 3; pp. 3847 - 3855
Main Authors: Xiong, Guojiang, Sun, Shunshun
Format: Journal Article
Language:English
Published: New York IEEE 01.09.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Accuracy
Analytical model
Analytical models
Binary codes
biogeography-based optimization (BBO)
Circuit breakers
Circuit faults
Cognition
fault section diagnosis (FSD)
information correction
Linear programming
Mathematical models
Power systems
Protective relaying
SCADA systems
Transformers
ISSN:0018-9529, 1558-1721
Online Access:Get full text
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Summary:The diagnostic accuracy of analytical models for fault section diagnosis of power systems relies heavily on the correction of protective relays (PRs) and circuit breakers (CBs). The current analytical models use the received alarm information directly, but the actions of PRs and CBs are fraught with uncertainties of mal-operation and miss-operation, and they are also subject to change during the uploading process, which may result in wrong results. To address this issue, this study presents an information correction method to correct those wrong or unreasonable PRs and CBs. Different abnormal action situations of PRs and CBs for busbars, lines, and transformers are considered and used to derive the corresponding correction strategies. Besides, an improved biogeography-based optimization based on binary coding and Boolean operations is developed to solve the analytical model. Simulations on two power systems indicate the accuracy of the analytical model and the superiority of the solving method.
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ISSN:0018-9529
1558-1721
DOI:10.1109/TR.2025.3549059