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Record W2501356004 · doi:10.1109/tie.2016.2586019

Optimal Low Switching Frequency Pulsewidth Modulation of Current-Fed Three-Level Converter for Solar Power Integration

2016· article· en· W2501356004 on OpenAlexaff
Amarendra Edpuganti, Akshay Kumar Rathore, Dipti Srinivasan, Carlo Cecati, Concettina Buccella

Bibliographic record

VenueIEEE Transactions on Industrial Electronics · 2016
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsConcordia University
Fundersnot available
KeywordsTotal harmonic distortionPulse-width modulationPhotovoltaic systemInverterElectronic engineeringModulation (music)Power (physics)HarmonicNetwork topologyComputer scienceSwitching frequencyCurrent sourceElectrical engineeringVoltageEngineeringPhysics

Abstract

fetched live from OpenAlex

Large-scale photovoltaic energy conversion systems have been installed at many places across the world and they handle higher power levels. In high power conversion, low device switching frequency operation is preferred in order to satisfy the thermal constraints of semiconductor devices and also to improve efficiency. However, low device switching frequency operation leads to higher total harmonic distortion (THD) of the converter output currents. Synchronous optimal pulsewidth modulation (SOP) is an emerging low device switching frequency modulation technique, which has been successfully implemented for voltage source inverters without compromising on THD. The goal of our research is to propose, analyze, and implement a modified SOP technique for current source inverter topologies. The additional switching constraints for these inverter topologies have been included in the modified SOP technique. The experimental results obtained from a low-power prototype demonstrated its effectiveness.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.917
Threshold uncertainty score0.936

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 head0.045
GPT teacher head0.248
Teacher spread0.204 · 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 designOther design
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

Citations20
Published2016
Admission routes1
Has abstractyes

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