Dual‐setting characteristic for directional overcurrent relays considering multiple fault locations
Bibliographic record
Abstract
Optimal relay settings are determined where coordination constraints are modelled considering only either one fault location (near end or midpoint) or two fault locations (near and far end) on a feeder. This study, first, investigates whether considering one or two fault locations is sufficient to guarantee proper coordination for faults at all other locations on a feeder. The results show that violations, in the coordination constraints, can occur at various points along the feeder if the relays are coordinated considering one or two fault locations. In addition, considering multiple fault locations while determining the optimal relay setting can avoid such problem but on the expense of the overall relay tripping time. Thus, a dual‐setting characteristic for directional overcurrent relays (DOCRs) is proposed instead of the conventional inverse time‐current characteristic. The study is conducted on the power transmission system of IEEE 24‐bus and the power distribution system of IEEE 14‐bus. The proposed characteristic achieves notable reduction in total DOCRs operating time over the conventional characteristic for both test systems while achieving proper coordination across a broader range of possible fault locations.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".