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Record W2807180842 · doi:10.1109/icps.2018.8369962

A new multi-port active DC-link for PMG-based WECSs

2018· article· en· W2807180842 on OpenAlexaff
X. F. St. Onge, K. McDonald, Christian M. Richard, S. A. Saleh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsTotal harmonic distortionElectrical engineeringConvertersVoltageAC powerPulse-width modulationComputer scienceElectronic engineeringTopology (electrical circuits)Engineering

Abstract

fetched live from OpenAlex

This paper presents the development and performance evaluation of a new active multi-port dc-link for applications in permanent magnet generator (PMG)-based wind energy conversion systems (WECSs). The proposed dc-link is developed as a mid-stage between a three phase (3φ) multilevel ac-dc generator-side power electronic converter (PEC) and a 3φ 6-pulse dc-ac grid-side PEC. The design of the dc-link is based on a multi-port converter (MPC) topology with two dc-dc PECs, which have their outputs connected in parallel. Each dc-dc PEC is operated and controlled independently, in order to achieve separate voltage-transfer ratios, along with the possibility of processing continuous or discontinuous input dc voltages. The performance of the MPC active dc-link is evaluated in experiments for a 7.5 kW PMG-based WECS under different operating conditions. Test results show that the proposed dc-link is capable of producing a high quality regulated dc voltage over a wide range of wind speeds, and increasing the extracted power from the PMG. Performance results also demonstrate that the operation of the MPC active dc-link has minor impacts on the harmonic distortion at the terminals of the PMG, along with negligible impacts on the operation and control of the grid-side PEC.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.023
GPT teacher head0.262
Teacher spread0.240 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations5
Published2018
Admission routes1
Has abstractyes

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