A High-Power High-Ratio DC-DC Converter with DC Fault Blocking Capability
Bibliographic record
Abstract
This paper proposes a non-isolated medium-voltage DC-DC converter with high step-up ratio. It aims to interconnect the low-voltage (LV) generation units and medium-voltage (MV) power-collecting grid in DC renewable system. The proposed DC-DC converter is composed by a switch network and a few cells. The switch network alternatively configures the cells in parallel connection for charging from low-voltage input side (VL) and in series connection for discharging to high-voltage output side (VH). This helps step up the low generation-unit voltage to power-collecting-grid level. Meanwhile, the embedded cells in converter possess voltage adjusting ability, which enables the immediate change of output voltage. As compared to other megawatt-class non-isolated DC-DC converter, the proposal not only achieve high step-up ratio, but also integrates the capabilities of output voltage modulation and DC fault blocking. The feasibility of the proposed DC-DC converter is verified by simulations performed in MATLAB/SIMULINK.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".