Compensation Method for Parallel and Iterative Real-Time Simulation of Electromagnetic Transients
Bibliographic record
Abstract
Parallelization allows accelerating the computation of Electromagnetic Transients (EMTs). It can rely on the natural propagation delay of transmission lines (line-delay) to decouple a network into sub-networks without any loss of accuracy. Other techniques have to be used when there is no line-delay available. This paper presents one of them, using the Compensation Method (CM). This method is applied to decouple and parallelize real-time EMT simulations. The main novelty towards previous works is the introduction of an iterative version of CM to handle nonlinearities. The performance and accuracy of CM is studied through test cases, including practical distribution and High Voltage Direct Current (HVDC) networks. Hardware-In-the-Loop (HIL) setups with Line-Commutated Converters (LCC) and Voltage Source Converters (VSC) are used to test the iterative CM on practical real-time nonlinear cases.
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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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".