Multi-Rate Mixed-Solver for Real-Time Nonlinear Electromagnetic Transient Emulation of AC/DC Networks on FPGA-MPSoC Architecture
Bibliographic record
Abstract
Nonlinear phenomena widely exist in AC/DC power systems, which should be accounted for accurately in real-time electromagnetic transient (EMT) simulation for obtaining precise results for hardware-in-the-loop applications. However, iterative solutions such as the Newton-Raphason method that can precisely obtain the results for highly nonlinear elements, are time consuming and computationally onerous. To fully utilize the time space and optimize hardware computation resources without loss of accuracy, this work proposes a novel multi-rate mixed-solver for AC/DC systems, wherein both iterative and non-iterative solvers with different time-steps are applied to the decomposed subsystems, and the linear solvers are reused within each time-step. The proposed solver and the complete real-time emulation system are implemented on FPGA-MPSoC platform. The real-time results are captured by the oscilloscope and verified with PSCAD/EMTDC and SaberRD for system-level and device-level performance evaluation.
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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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".