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 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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Publication Details

Journal
IEEE Transactions on Reliability
Published
2025-03-28
DOI
https://doi.org/10.1109/tr.2025.3549059
Primary Topic
Advanced Computational Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

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

S. Sun, Guojiang Xiong
IEEE Transactions on Reliability
Advanced Computational Techniques and Applications
article

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

S. Sun, Guojiang Xiong
article en

Abstract

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.

IEEE Transactions on ReliabilityVol. 74(3)
Guizhou University (CN), Guizhou Electric Power Design and Research Institute (CN)
National Natural Science Foundation of China
Climate action
Openalex Percentile: Top 97%
Advanced Computational Techniques and Applications
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