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Record W2810651452 · doi:10.1109/tie.2018.2850035

An Enhanced Closed-Loop Control Strategy With Capacitor Voltage Elevation for the DC–DC Modular Multilevel Converter

2018· article· en· W2810651452 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Industrial Electronics · 2018
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCapacitorVoltageĆuk converterForward converterCharge pumpDC biasModular designFlyback converterDirect currentElectronic engineeringMaximum power transfer theoremControl theory (sociology)Electrical engineeringBoost converterComputer scienceEngineeringPower (physics)Topology (electrical circuits)PhysicsControl (management)

Abstract

fetched live from OpenAlex

The dc-dc modular multilevel converter (MMC), derived from the ac-dc MMC, is an attractive converter topology for interconnection of medium-/high-voltage dc grids. The dc-dc MMC generates an ac voltage component in each arm to drive an ac circulating current for maintaining the energy balance of its submodule capacitors. The power transfer capability of the dc-dc MMC and the amplitude of the ac circulating current are closely coupled with the available arm ac voltage headroom. As the voltage conversion ratio of the dc-dc MMC deviates from 0.5, the power transfer capability of the converter diminishes. This paper proposes an enhanced closed-loop control strategy, which increases the power transfer capability and at the same time reduces the ac circulating current of the dc-dc MMC. Performance and effectiveness of the proposed control strategy are demonstrated by simulation studies in the MATLAB/Simulink as well as experiments conducted on a laboratory prototype.

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.

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: none
Teacher disagreement score0.866
Threshold uncertainty score0.881

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 integrity0.0000.001
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 head0.023
GPT teacher head0.240
Teacher spread0.217 · 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