A dual active bridge DC-DC converter with optimal DC-link voltage scaling and flyback mode for enhanced low-power operation in hybrid PV/storage systems
Bibliographic record
Abstract
Today's PV micro-inverters (MIVs) provide a modular solution for generation, however the energy storage architectures remain centralized, requiring an additional bi-directional ac-dc converter, with complex cell balancing circuits. Distributing storage capacity within the smart PV panels allows power fluctuations to be locally buffered, while minimizing the need for additional power electronics and balancing circuits. The dual-active-bridge (DAB) topology, which is adopted in this paper, provides bi-directional power flow; however it generally suffers from poor efficiency at low power. It is shown that with a minor modification, the DAB can be operated as a two-transistor flyback converter for improved efficiency. In addition, the dc-link voltage can be dynamically adjusted for the best performance in DAB mode. The proposed control scheme is demonstrated on a 100 W prototype, with up to 8% increase in efficiency at low power.
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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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".