Algorithm to Prevent Breaker-Failure Protection Maloperation Due to Subsidence Current
Bibliographic record
Abstract
Duplication of circuit breakers (CBs) in substations is not realistic due to economic and operational constraints. In the event of failure of a CB, adjacent breakers need to be called in to isolate the fault. Typically, a breaker-failure protection (BFP) function is integrated within commercial relays to monitor such situations. However, these functions are prone to maloperation because of subsidence in current transformers (CTs) resulting from faults with significant decaying dc component. To this end, a reliable reset algorithm for the BFP function is presented. After measuring the decaying dc component within a one-cycle moving window, the proposed algorithm accurately distinguishes between the alternating pattern of fault current and exponential decaying pattern in subsidence current. Its performance remains unaffected during change in fault current level, decaying dc component, CT saturation, level of subsidence, and random noise. Effectiveness of the proposed scheme in practical scenarios is demonstrated through a hardware setup validated through error analysis. Overall performance evaluation in terms of reliability indices testifies its superiority over available techniques.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".