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Record W4361286169 · doi:10.18280/jesa.560107

Photovoltaic Source Powered Shunt Active Power Filter Optimized by Cuckoo Search Algorithm

2023· article· en· W4361286169 on OpenAlexvenueno aff
Mohamed Khelil Cherfi, Abderrezak Gacemi, Abdelkader Morsli, Abdelhalim Tlemçani

Bibliographic record

VenueJournal Européen des Systèmes Automatisés · 2023
Typearticle
Languageen
FieldEngineering
TopicPower Quality and Harmonics
Canadian institutionsnot available
Fundersnot available
KeywordsCuckoo searchPhotovoltaic systemComputer scienceShunt (medical)Electronic engineeringAlgorithmElectrical engineeringEngineeringMedicine

Abstract

fetched live from OpenAlex

Non-linear loads such as computers, televisions, arc furnaces, inverters, etc. generates harmonic currents infecting the quality of the power supply and causing damage.To remedy this problem, the shunt active power filter presents the best way to fight against harmonic currents.This paper gives a new technique of shunt active power filter which has tested to be the satisfactory answer to improve energy high-quality in phrases of removing harmonics caused by means of non-linear power loads distribution networks.Our work presents an SAPF powered by a photovoltaic system whose energy control is managed via metaheuristic cuckoo search optimization as the fastest and most reliable optimization unlike traditional strategies like the Perturb and Observe (P&O) algorithm used as the MPPT for PV systems, which gives us a stable power supply to further eliminate harmonics.The simulation on the Matlab Simulink environment truly suggests that the proposed model improves the excellent quality of energy and the control method is efficient and in accordance to the international standard recommendations IEEE 519-1992.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.856
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.023
GPT teacher head0.259
Teacher spread0.236 · 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; both teacher heads agree on what is shown here.

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
Published2023
Admission routes1
Has abstractyes

Explore more

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