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Record W2769546001 · doi:10.23919/cjee.2017.8048409

Derivation of multilevel voltage source converter topologies for medium voltage drives

2017· article· en· W2769546001 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

VenueChinese Journal of Electrical Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNetwork topologyTopology (electrical circuits)Modularity (biology)ConvertersComputer scienceVoltageCapacitorEngineeringElectrical engineeringComputer network

Abstract

fetched live from OpenAlex

Multilevel voltage source converters(MLVSCs) have been widely applied in the medium voltage drive(MVD) industry. The performance of a MVD system is strongly dependent on the utilized topology. As of today, many interesting topologies have been proposed and evaluated in literature. In addition to proposing new topologies, another important research topic is the MLVSC topology derivation. In this paper, two topology derivation principles, i.e. horizontal conformation principle and vertical conformation principle, are proposed from the standpoint of modularity. In both principles, a MLVSC topology can be considered as a certain combination of one base switching cell and several module switching cells. With the proposed principle, the derived topology will naturally have modularity, which is favorable in practical applications. In addition, voltage level extension based on cascaded H-bridge building blocks(HBBBs) is also introduced. The challenging issues faced by the emerging topologies for MVD applications are also discussed. It is hoped that this paper can provide a new perspective on the MLVSC topology derivation and inspire new topologies in the future.

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)0.001
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 score0.900
Threshold uncertainty score0.818

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.012
GPT teacher head0.241
Teacher spread0.229 · 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