A phase-domain synchronous machine model with constant equivalent conductance matrix for EMTP-type solution
Bibliographic record
Abstract
Interfacing machine models in either nodal analysis-based (EMTP-like) or state variable-based transient simulation programs plays an important role in numerical accuracy and computational performance of the overall simulation. As an advantageous alternative to the traditional qd models, a number of advanced phase-domain (PD) and voltage-behind-reactance (VBR) machine models have been recently introduced. However, the rotor-position-dependent conductance matrix in the machine-network interface complicates the use of such models in EMTP. This paper focuses on achieving constant and efficient interfacing circuit for the PD synchronous machine model. It is shown that the machine conductance matrix can be formulated into a constant sub-matrix plus a time-variant sub-matrix. Eliminating numerical saliency from the second term results in a constant conductance matrix of the proposed PD model, which is a very desirable property for the EMTP solution since the re-factorization of the network conductance matrix at every time step is avoided. Case studies demonstrate that the proposed PD model represents a significant improvement over other established models used in EMTP while preserving the accuracy of the original/classical PD model.
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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) | 0.000 | 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) | 0.005 | 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".