Approximate Voltage-Behind-Reactance Induction Machine Model for Efficient Interface With EMTP Network Solution
Bibliographic record
Abstract
A so-called voltage-behind-reactance (VBR) induction machine model has recently been proposed for the Electro-Magnetic Transient Program (EMTP) solution as an advantageous alternative to the traditionalqdand phase-domain (PD) models. This paper focuses on achieving an efficient interface of the machine models with the EMTP network. It is shown first that a discretized PD model can be formulated to have a constant machine conductance submatrix, which is a very desirable numerical property that allows avoiding the re-factorization of the network conductance matrix at every time step. Furthermore, an approximate voltage-behind-reactance (AVBR) model is proposed where the rotor-speed-dependent coefficients are neglected, thus leading to a similar constant machine conductance submatrix and efficient interface. Case studies demonstrate that the new AVBR model represents a significant improvement in terms of numerical accuracy and efficiency over other established models used in EMTP.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.003 | 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".