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Record W2548919962 · doi:10.1109/tpel.2016.2623568

A New Six-Switch Five-Level Active Neutral Point Clamped Inverter for PV Applications

2016· article· en· W2548919962 on OpenAlexafffund
Hongliang Wang, Lei Kou, Yan‐Fei Liu, Paresh C. Sen

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2016
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTopology (electrical circuits)InverterPhotovoltaic systemAC powerCapacitorElectronic engineeringModulation (music)Network topologyPower (physics)CapacitanceComputer scienceVoltageEngineeringElectrical engineeringPhysicsElectrode

Abstract

fetched live from OpenAlex

Multilevel inverters are one of the preferred solutions for medium-voltage and high-power applications and have found successful industrial applications. Five-level active neutral point clamped inverter (5L-ANPC) is one of the most popular topologies among five-level inverters. A six-switch 5L-ANPC (6S-5L-ANPC) topology is proposed. Compared to the conventional 5L-ANPC inverters, the 6S-5L-ANPC reduces two active switches and has lower conduction loss. The proposed modulation enables the 6S-5L-ANPC inverter to operate under both active and reactive power conditions. The flying-capacitor capacitance is designed under both active and reactive power conditions. The analysis shows the proposed topology is suitable for photovoltaic grid-connected applications. A 1 KVA single-phase experimental prototype is built to verify the validity and flexibility of the proposed topology and modulation method.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.013
GPT teacher head0.223
Teacher spread0.210 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations167
Published2016
Admission routes2
Has abstractyes

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