Line-to-Line Short-Circuit-Based Finite-Element Performance and Parameter Predictions of Large Hydro Generators
Bibliographic record
Abstract
A two-dimensional time-stepped finite-element (FE) method is used to model and successfully replicate saturated line-to-line and three-phase short-circuit test responses recorded on a 40-pole 13.75 MVA hydro generator at Hydro-Quebec's Rapides-des-Quinze generating station. Three levels of line-to-line and sudden three-phase short-circuit tests (0.13, 0.25, and 0.48 p.u.) are simulated numerically using the FE-based model. While symmetrical faults are only used for parameter determination, the computed line-to-line waveforms are thoroughly compared to real data, with a special attention given to field current responses. According to IEEE Standard 115-1995, the d-axis dynamic reactances and time constants are computed from three-phase short-circuit tests, while the negative-sequence reactance is derived from the line-to-line short-circuit test resulting in a rated armature current. The obtained simulated test responses and parameter values, from both symmetrical and asymmetrical faults, support the effectiveness of the proposed FE-based model in incorporating the saturation phenomenon, large number of poles, and detailed damper representation to achieve an accurate dynamic performance assessment together with negative-sequence reactance and dynamic constants prediction.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".