Stability Evaluation of Interpolation, Extrapolation, and Numerical Oscillation Damping Methods Applied in EMT Simulation of Power Networks With Switching Transients
Bibliographic record
Abstract
For Electro-Magnetic-Transient (EMT) simulations of power networks with switches, techniques such as linear interpolation and Critical Damping Adjustment (CDA) are widely used for improving numerical robustness. This paper analyzes the numerical stability of simulations with these techniques. Firstly, it is mathematically shown that the interpolation or CDA step is equivalent to the introduction of additional switching states. Subsequently, Common Quadratic Lyapunov Function (CQLF) theory is used to investigate the numerical stability of the whole simulation considering these new switching states. It is proved that the widely used strategies like linear interpolation and CDA always result a stable simulation if the original switched system is strictly passive in all switching states. Finally, it is shown that the developed approach can be used to determine the stability of other practical interpolation methods. Examples are provided to verify the proposed technique.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".