A validation methodology for real time model of modular multilevel converter
Bibliographic record
Abstract
Modular multilevel converter (MMC) is a promising topology for medium and high power applications. The MMC system consists a large number of sub-modules (SMs), which take long time to simulate. In a real-time simulator, the MMC model is optimized to have a fast simulation speed for real-time applications, such as hardware-in-the-loop (HIL) tests. The methodology to evaluate model fidelity is important. In this paper, a methodology is proposed to validate an MMC model capable of real time simulation and implemented in central processing unit (CPU) and field-programmable gate array (FPGA). The model is validated in both open-loop and closed-loop control in a simple MMC test system, and compared to a reference detailed model made with SimPowerSystems (SPS) blocks. The effect of the model sampling time on the accuracy is also studied. The results indicate the MMC model optimized for real time simulation with a time step of 25 μs is as accurate as an SPS model with a time step of 0.2 μs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".