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Comprehensive Design of a Grid-Connected Seven-Switch Boost-Type Current Source PV Inverter

2021· article· en· W3208771960 on OpenAlexafffund
Kawther Ezzeddine, Mahmoud Hamouda, Hadi Y. Kanaan, Kamal Al‐Haddad

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsÉcole de Technologie Supérieure
FundersAgence Universitaire de la Francophonie
KeywordsInverterPhotovoltaic systemComputer sciencePower (physics)Topology (electrical circuits)GridElectrical engineeringVoltagePhysicsEngineeringMathematics

Abstract

fetched live from OpenAlex

In this paper a grid-connected three-phase seven-switch boost-type photovoltaic (PV) current source inverter (CSI7) is investigated. The designed CSI7 injects sinusoidal currents into the grid with a peak amplitude <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">${\hat I_g} = 7.71A$</tex> for a maximum PV input-power <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">${P_{pv - MPP}} = 3.6kW$</tex> at <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">${V_{pv - MPP}} = 432.48V$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">${I_{pv - MPP}} = 8.32A$</tex> . The principle of operation is thoroughly described and the voltage and current stresses on the semiconductor power devices are analytically determined. Calculation formula for the design of the passive components are also provided. These calculations are performed based on the inverter's rated operating conditions and their accuracy is verified by digital computer simulations. Accordingly, proper active and passive components are selected and a 3. 6 kW PV-CSI7 is designed. The performance of the designed inverter are evaluated under ideal operating conditions <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\left({{T_a} = 25^\circ C,G = 1000W/{m^2}} \right)$</tex> and under shading conditions. An overall efficiency around 98 % is obtained.

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 score0.894
Threshold uncertainty score0.898

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)0.0010.000

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 head0.039
GPT teacher head0.236
Teacher spread0.197 · 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

Citations3
Published2021
Admission routes2
Has abstractyes

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