The experimental performance of a multi-level AC-DC power electronic converter for PMG-based WECSs
Bibliographic record
Abstract
This paper experimentally tests a new multi-level generator-side ac-dc power electronic converter (PEC) for applications in permanent magnet generator (PMG)-based wind energy conversion systems (WECSs). The tested generator-side PEC is designed as a cascaded H-bridge multi-level PEC, and is fed by one 3φ supply. The used H-bridge cells are modified such that each cell is composed of a forward half-bridge and a backward half-bridge. The forward half-bridge produces a dc voltage, while the backward half-bridge provides a path for the current to flow to the next H-bridge cell (connected in series). The new multi-level ac-dc PEC is implemented for experimental testing as a generator-side ac-dc PEC in a 7.5 kW PMG-based WECS. The tested acdc PEC is operated using switching signals that are generated by the sinusoidal level-shifted pulse width modulation strategy. Experimental test results demonstrate reduced harmonic distortion in input currents, efficient and high quality power transfer from the PMG to the dc link, and high input power factor.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".