MétaCan
Menu
Back to cohort
Record W4319998282 · doi:10.18280/jesa.550610

Comparison Analysis of Different Grid-Connected PV Systems Topologies

2022· article· fr· W4319998282 on OpenAlexvenueno aff
Khalil Benmouiza

Bibliographic record

VenueJournal Européen des Systèmes Automatisés · 2022
Typearticle
Languagefr
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsNetwork topologyGridPhotovoltaic systemComputer scienceTopology (electrical circuits)Electrical engineeringMathematicsEngineeringComputer network

Abstract

fetched live from OpenAlex

Nowadays, photovoltaic systems are more and more often connected to the electricity grid.They allow a household to produce part of its electricity in a clean way and to inject excess electricity production into the network.Higher output voltage and Maximum Power Point Tracking (MPPT) for each solar panel are attracting increased interest in photovoltaic solar systems with integrated converters coupled in series and parallel.In this paper, different PV arrays and converters architectures are tested in order to obtain maximum delivered power for the grid.The analysis of the output current, voltages, and power for each part of the grid-connected PV systems is analysis considering the parallel and series combination of PV arrays and DC/DC converters to extract useful information of such systems.Moreover, the performance comparison of each topology is elaborated in both cases; clear and cloudy skies.The obtained results show that using parallel configurations gives more power than series ones.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.033
GPT teacher head0.294
Teacher spread0.261 · 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 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

Citations5
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal Européen des Systèmes AutomatisésSame topicPhotovoltaic System Optimization TechniquesFrench-language works237,207