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Record W2093476204 · doi:10.1109/tpel.2014.2352649

A Novel and Simple Single-Phase Modulator for the Nested Neutral-Point Clamped (NNPC) Converter

2014· article· en· W2093476204 on OpenAlexaff
Mehdi Narimani, Bin Wu, Zhongyuan Cheng, Navid R. Zargari

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2014
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCapacitorTopology (electrical circuits)Electronic engineeringEngineeringNetwork topologyVoltageControl theory (sociology)Electrical engineeringComputer scienceControl (management)Computer network

Abstract

fetched live from OpenAlex

The nested neutral-point clamped (NNPC) converter is a four-level converter topology for medium-voltage applications with interesting properties such as operating over a wide range of voltages (2.4-7.2 KV) without the need for connecting the power semiconductor in series, high quality output voltage, and less number of components in compare to other classical four-level topologies. The control and balance of the flying capacitors (FCs) of the NNPC converter can be done by different control techniques taking advantage of the large number of redundant switching states. This paper presents a simple single-phase modulator for the NNPC converter, which can be applied to each phase of a three-phase NNPC converter. The proposed simple technique can control and balance the FCs to their desired values. Performance of the proposed technique under different operating conditions is investigated in the MATLAB/Simulink environment. The feasibility of the proposed converter is evaluated experimentally.

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 score0.954
Threshold uncertainty score0.906

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 integrity0.0000.000
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 head0.015
GPT teacher head0.228
Teacher spread0.213 · 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

Citations47
Published2014
Admission routes1
Has abstractyes

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