A new three-phase AC/DC high power factor soft-switched step-up converter with high gain rectifier modules for medium voltage grid in wind systems
Bibliographic record
Abstract
This paper presents a new single-stage AC/DC step-up soft-switched converter for medium voltage (MV) DC grid for wind energy systems. To achieve close-to-unity power factor, stepping up the voltage and reduce the number of conversion stages, a three-phase boost AC/DC rectifier and a high frequency step-up resonant converter with high gain rectifier modules are combined into a single-stage step-up converter. As a result, the proposed converter is capable to achieve very high voltage gain efficiently without using bulky high turns ratio step-up transformer. Soft switching operation is achieved by using multiple resonant circuit modules. The voltage stress of each power switch is also reduced to half of the DC-link voltage by using a series connection of two strings of switch pairs. In addition, the proposed converter is capable to regulate the output MV grid voltage by utilizing a combination of duty cycle and variable switching frequency control. Results are given on a 1.5MW, 690Vac/40kV system to highlight the merits of the proposed converter.
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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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".