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Record W2541218246 · doi:10.1109/smart.2015.7399224

Comparative study between the improved schemes of MAF-based robust PLLs

2015· article· en· W2541218246 on OpenAlexaff
Mohamed Mellouli, Mahmoud Hamouda, Jaleleddine Ben Hadj Slama, Kamal Al‐Haddad

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsComputer scienceControl theory (sociology)Artificial intelligenceControl (management)

Abstract

fetched live from OpenAlex

Phase-Looked loop (PLL) is nowadays the best suited technique to achieve grid synchronization. The Moving Average Filter (MAF) based PLLs have received in recent three years considerable attention owing to their attractive features. Indeed, they are able to completely eliminate the unwanted effect of harmonics, dc offset, and unbalanced voltages. Unfortunately, these advantages are paid in term of open-loop bandwidth reduction which worsens the system's dynamic response. To overcome this limitation, a variety of improved MAF-PLLs schemes were developed to improve the dynamic response. The main objective of this paper is therefore to perform an assessment and a comparative study between the performances these new improved PLL schemes. The proposed study is based on numerical simulation carried out for five cases of grid disturbances.

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 score0.175
Threshold uncertainty score0.197

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 head0.042
GPT teacher head0.244
Teacher spread0.202 · 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
Published2015
Admission routes1
Has abstractyes

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