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

• 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
• DOI: 10.1109/TR.2025.3549059

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.