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Record W4387682260 · doi:10.1109/jestpe.2023.3324873

Multiplexed-Stack Converter With DC-Fault Ride-Through Capability and High Compactness

2023· article· en· W4387682260 on OpenAlexafffund
Levi Bieber, Liwei Wang, Juri Jatskevich

Bibliographic record

VenueIEEE Journal of Emerging and Selected Topics in Power Electronics · 2023
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStack (abstract data type)Compact spaceMultiplexingElectrical engineeringElectronic engineeringFault (geology)Computer scienceMaterials scienceTopology (electrical circuits)EngineeringMathematics

Abstract

fetched live from OpenAlex

This article presents a new multiplexed-stack converter (MSC) for high-voltage direct-current (HVDC) power conversion. The MSC reduces the number of stacks of submodules (SMs) needed for three-phase alternating-current (AC) systems from six, as in conventional modular multilevel converters (MMCs), to four, which can substantially decrease the size of converter stations. The MSC comprises two full-bridge SM (FBSM)-based Outer stacks, two half-bridge SM (HBSM)-based Inner SM stacks, and director-switch (DS) valves to generate sinusoidal three-phase AC voltages. The MSC offers several benefits over existing converters: it can handle and block DC faults due to its FBSM-based Outer stacks, it can attain high efficiency due to its HBSM-based Inner stacks, and it can ease valve design due to fundamental-frequency and zero-voltage-switching (ZVS) operation of its DSs. A sweet-spot operating voltage is derived where the Outer and Inner stack energies are naturally balanced without the need of DC pole capacitors (PCs). For deviations from the sweet-spot voltage, DC-side PCs enable energy balancing for the stacks. This article presents HVDC-scale simulations and reduced-scale hardware experiments that confirm the MSC’s performance in real and reactive power conversion. This article also contrasts the MSC with other state-of-the-art converters, indicating its competitive efficiency and compactness.

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 score0.750
Threshold uncertainty score0.818

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 head0.010
GPT teacher head0.234
Teacher spread0.224 · 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

Citations2
Published2023
Admission routes2
Has abstractyes

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