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Record W3199097527 · doi:10.18280/ejee.230404

Design of a New Duty Cycle Modulation to Improve the Energy Quality of an Insulated Production System

2021· article· en· W3199097527 on OpenAlexvenueno aff
Clément Kengnou Donfack, Charles Hubert Kom, Jean Jacques Mandeng, Paune Felix

Bibliographic record

VenueEuropean Journal of Electrical Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsnot available
Fundersnot available
KeywordsInverterDuty cyclePulse-width modulationTotal harmonic distortionControl theory (sociology)HarmonicVoltageThree-phaseModulation (music)MATLABHarmonicsComputer scienceEngineeringControl (management)Electrical engineeringPhysics

Abstract

fetched live from OpenAlex

In this article, we propose a new strategy for controlling three-phase inverters of renewable energy sources, based on the Duty Cycle Modulatiom (DCM) control using the Park and Fortescue transformation (DCM-dq-dih). Our goals in setting and using this strategy are, on the one hand, to induce a lower harmonic rate as compared to the SPWM (Sinusoidal Pulse Width Modulation) strategy and on the other hand, this control technique enables the inverter to deliver balanced voltages, be it in the event of load unbalance. Our design is built on the basis of the known mode of DCM control of single-phase inverters. Thus, the control of our three-phase inverter is carried out by three DCM modules whose set-points come from the direct, reverse and homopolar strings reconstructed in a Park landmark. This new strategy was tested on the MATLAB Simulink environment for a load of 160 kW. The test results show a reduced Total Harmonic Distorsion (THD) of 2.7 times compared to the THD produced by the SPWM control strategy. In addition, regulation of the symmetrical components during load unbalance is ensured so that the inverter always delivers constant and balanced voltages.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.712
Threshold uncertainty score0.363

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.019
GPT teacher head0.209
Teacher spread0.190 · 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
Published2021
Admission routes1
Has abstractyes

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