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Record W1499913891 · doi:10.1109/apec.2015.7104443

Ripple voltage minimization in single phase floating bridge converter modules using a Transformer Coupled Asymmetrical bridge converter

2015· article· en· W1499913891 on OpenAlexafffund
R. Ul Haque, Shuai Leng, Nirmana Perera, John Salmon

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsUniversity of Alberta
FundersUniversity of Alberta
KeywordsRippleCapacitorConvertersTransformerVoltageElectronic engineeringElectrical engineeringComputer scienceEngineering

Abstract

fetched live from OpenAlex

A method for reducing the capacitor size used in single phase floating capacitor voltage source converter modules is presented. A Transformer Coupled Asymmetrical half-Bridge (TCAB) is used to exchange energy between the capacitor regulated dc sources of the main power converter modules, without using separate power sources. This energy exchange (bidirectional) compensates for naturally occurring low frequency voltage ripple in the floating capacitor main power converters. This enables smaller film dc capacitors to be used. The latter can be used to reduce the overall system size/cost with a longer system working lifetime. The ripple voltage reduction and voltage balancing features provided is not intended to be specific to a particular modular power converter system, MMC systems are an example, but are illustrated here using utility connected single phase floating converters. The switching control methods described avoid the use of extra filter components and to maximize the average current used to transfer energy between the modules. Simulations and experimental results are presented to validate the operation and performance of the proposed system with the emphasis placed on the voltage ripple reduction feature.

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: none
Teacher disagreement score0.929
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.056
GPT teacher head0.274
Teacher spread0.218 · 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

Citations1
Published2015
Admission routes2
Has abstractyes

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