Artificial neural network applications for power system protection
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Bibliographic record
Abstract
The most commonly used systems for protecting transmission and subtransmission lines belong to the family of distance relays. Over the past eighty years, successful designs based on electromechanical, solid-state and digital electronics technologies have been produced and marketed. These relays implement various characteristics, such as impedance, offset-impedance, admittance, reactance and blinders. The artificial neural network based designs of distance relays proposed so far work well for ideal fault conditions but are not able to maintain the integrity of the boundaries of the relay characteristics of generic designs. This paper reviews ANN models that have been proposed in the past for protecting components of power systems and presents a methodology that fully exploits the potential of ANNs in designing generic distance relays that retain the integrity of the boundaries of their characteristics
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it