MétaCan
Menu
Back to cohort
Record W4294832582 · doi:10.3390/electronics11172779

Conception and Experimental Validation of a Standalone Photovoltaic System Using the SUPC5 Multilevel Inverter

2022· article· en· W4294832582 on OpenAlexaff
Hind El Ouardi, Ayoub El Gadari, Youssef Ounejjar, Kamal Al-Haddad

Bibliographic record

VenueElectronics · 2022
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsTotal harmonic distortionPhotovoltaic systemCapacitorPulse-width modulationElectronic engineeringVoltageMaximum power point trackingMATLABInverterWaveformComputer scienceControl theory (sociology)EngineeringElectrical engineering

Abstract

fetched live from OpenAlex

In this work, an advanced pulse width modulation (PWM) technique was developed to provide the auto-balancing of the capacitors voltages of the five-level split-packed U-Cells (SPUC5) single-phase inverter, and then, the latter was applied to a photovoltaic (PV) system in standalone mode to evaluate its performance in this kind of application. The SPUC5 inverter makes use of only five switches (four active bidirectional switches and one four quadrant switch), one DC source and two capacitors to generate five levels of output voltage and a current with a quasi-sinusoidal waveform which reduces the total harmonic distortion (THD) without the need to add filters or sensors, and also reduces its cost compared to the other multilevel inverters. In the proposed system; the incremental conductance (INC) algorithm is combined with a DC/DC boost converter to reach the maximum power (MP) of the PV array by tracking the MP point (MPP). The offered concept has been constructed and then simulated in the MATLAB/Simulink environment to evaluate its efficiency. According to the results, the self-balancing of the capacitors voltages has been achieved. A comparative study was performed with the traditional PWM technique. The proposed PV system has been validated by experimental results.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.760
Threshold uncertainty score0.381

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 head0.016
GPT teacher head0.226
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 teacher head, 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

Citations4
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueElectronicsSame topicMultilevel Inverters and ConvertersFrench-language works237,207