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Record W4386070837 · doi:10.11159/eee23.107

Control of Cascaded PV-Ćuk Converter Modules by Particle Swarm Optimization under Partial Shading Conditions

2023· article· en· W4386070837 on OpenAlexvenueno aff
Mohamed Etarhouni, Benjamin Chong

Bibliographic record

VenueProceedings of the World Congress on Electrical Engineering and Computer Systems and Science · 2023
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsShadingParticle swarm optimizationComputer scienceControl theory (sociology)Control (management)Artificial intelligenceAlgorithm

Abstract

fetched live from OpenAlex

This paper presents a particle swarm optimization (PSO) technique for the maximum power point tracking of a PV power generation system under unequal solar irradiation.The system consists of multiple PV-uk converter (PVCC) modules in a series chain and a terminal step-up converter for load connection.The bidirectional uk converter in each PVCC has two PV panels connected at its four terminals.The configuration offers the advantage that under shading or module mismatching, the uk converter provides a current bypass which can allow two PV panels track their available maximum power.The new PSO-based MPPT control scheme estimates the voltages corresponding to the maximum power each PV panel can generate under its specific weather conditions.Tuning of the controller parameters is based on the transfer function model of the proposed PVCC.The results show that the proposed PSO MPPT and modelbased control can ensure high performance maximum power generation regardless of shading conditions.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.150
Threshold uncertainty score0.384

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.008
GPT teacher head0.212
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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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