Saturable Voltage-Behind-Reactance Models of Induction Machines Including Air-Gap Flux Harmonics
Bibliographic record
Abstract
Accurate and numerically efficient models of induction machines are of critical importance for reliable analysis and simulation of large-scale power systems. Specifically, modeling magnetic saturation that causes air-gap flux harmonics, which can significantly affect machine dynamics, has been the focus of many research efforts. In this paper, two voltage-behind-reactance (VBR) models are proposed for induction machines which formulate the air-gap flux harmonics caused by the main flux saturation. Specifically, the proposed constant-parameter VBR (CPVBR) model can be conveniently interfaced with the external network using constantRLbranches and controlled voltage sources. The numerical performance of the two proposed VBR models is validated and benchmarked against the state-of-the-art models of induction machines with saturation and air-gap flux harmonics. It is shown that the proposed models offer superior numerical performance (i.e., higher accuracy and simulation speed) compared to the existing models, which would be beneficial for offline and/or real-time simulations of power systems.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".