Natural Sampling SVM-Based Common-Mode Voltage Reduction in Medium-Voltage Current Source Rectifier
Bibliographic record
Abstract
Conventional space vector modulation (SVM)-based common-mode voltage (CMV) reduction in medium-voltage (MV) current source rectifier (CSR) cannot be used in practice. Conventional SVM contains high-magnitude low-order harmonics, particularly the fifth and seventh harmonics, that are lying closely to the resonance frequency (4.5-5.5 p.u.) of the LC filter of the converter, thus, introducing resonance as the grid-side damping is small. Recently, a natural sampling SVM (NS-SVM) with superior low-order harmonics performance has been proposed for MV CSR. On this basis, a NS-SVM-based CMV reduction method is proposed for MV CSR in this paper. The proposed scheme achieves both good CMV reduction and superior low-order harmonics performance simultaneously. Additionally, effort to lower computational burden on calculating dwell times is made. Experiments are finally provided.
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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 | 0.001 |
| 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".