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Record W2542926794 · doi:10.1109/iecon.2009.5414962

Enhancing the three-phase synchronous reference frame PLL to remove unbalance and harmonic errors

2009· article· en· W2542926794 on OpenAlexaff
Suzan Eren, Masoud Karimi-Ghartemani, Alireza Bakhshai

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsQueen's University
Fundersnot available
KeywordsPhase-locked loopControl theory (sociology)Band-stop filterHarmonicRipplePhase (matter)Reference frameComputer scienceSIGNAL (programming language)Loop (graph theory)Filter (signal processing)Block (permutation group theory)Adaptive filterFrame (networking)Harmonic analysisAll-pass filterLow-pass filterElectronic engineeringEngineeringAcousticsMathematicsAlgorithmPhysicsVoltageTelecommunications

Abstract

fetched live from OpenAlex

This paper presents a modified three-phase phase locked loop, consisting of a multi-block adaptive notch filter (ANF) integrated into a conventional three-phase synchronous reference frame phase-locked loop (SRFPLL). The addition of the ANF to the system allows it to become frequency adaptive. Also, since the ANF consists of multiple blocks which are in parallel with one another, the system is able to remove multiple input signal distortions. Thus, the proposed system is able to eliminate the double frequency ripple that is normally caused in the conventional three-phase SRFPLL by input unbalance, as well as harmonic errors, despite the presence of frequency variations in the input signal. The proposed system is compared to a conventional three-phase SRFPLL, as well as a three-phase SRFPLL with a simple notch filter, and the advantages of the proposed system are discussed.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.008
GPT teacher head0.222
Teacher spread0.215 · 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

Citations37
Published2009
Admission routes1
Has abstractyes

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