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Record W7117742217 · doi:10.1109/tpwrd.2025.3649628

Coordination of Directional Overcurrent Relays in Transient Topologies Induced by Faster Operation of Remote-Side Circuit Breakers

2025· article· W7117742217 on OpenAlexaff
Mahdi Ghotbi-Maleki, Reza Mohammadi, Mahyar Abasi, Maher A. Azzouz

Bibliographic record

VenueIEEE Transactions on Power Delivery · 2025
Typearticle
Language
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsUniversity of Windsor
FundersQatar University
KeywordsOvercurrentCircuit breakerNetwork topologyRobustness (evolution)Transient (computer programming)Protective relayElectric power systemPower-system protectionTopology (electrical circuits)

Abstract

fetched live from OpenAlex

This paper presents a novel methodology for directional overcurrent relays (DOCRs) coordination that effectively accounts for the transient topologies triggered by faster operation of remote-side circuit breakers (CBs), thereby preventing miscoordination and enhancing power system reliability. The methodology is based on the dynamic model of DOCR, allowing for the incorporation of short-circuit currents associated with the moments before and after the operation of remote-side CB in the coordination process. This method facilitates the determination of time multiplier, pickup current, and characteristic curve settings; while earlier methods are unable to determine the latter two settings because updating these settings alters the slope of DOCR curve, shifting the specified interference between DOCRs on both sides of a line to a different fault location. The proposed method is structured as a nested optimization problem: the outer layer establishes the initial operational sequence of DOCRs on both sides of each line, while the inner layer updates the DOCR settings to prevent miscoordination. Comprehensive consideration of various short-circuit types and locations in the study about the faster operation of remote-side CB enhances the robustness of the proposed coordination method compare to existing ones, which is also validated through hardware-in-the-loop testing.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.588
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.240
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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