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Record W2624942421 · doi:10.1109/icps.2017.7945112

The experimental performance of a multi-level AC-DC power electronic converter for PMG-based WECSs

2017· article· en· W2624942421 on OpenAlexaff
S. A. Saleh, X. F. St. Onge, J. McLeod, W.M. McGivney

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsTotal harmonic distortionElectrical engineeringPulse-width modulationH bridgePower (physics)Power factorGenerator (circuit theory)VoltageConvertersAC powerModulation (music)Computer sciencePhysicsEngineeringAcoustics

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.800
Threshold uncertainty score0.510

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.031
GPT teacher head0.259
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations24
Published2017
Admission routes1
Has abstractyes

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