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Record W2166715811 · doi:10.1109/59.852148

New rotating transformation for efficient DSP control of active power-line conditioners

2000· article· en· W2166715811 on OpenAlexaff
L. Cheng, R. Cheung

Bibliographic record

VenueIEEE Transactions on Power Systems · 2000
Typearticle
Languageen
FieldEngineering
TopicPower Quality and Harmonics
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsAC powerElectric power transmissionElectronic engineeringComputer sciencePower controlPower (physics)VoltageLine (geometry)Electric power systemEngineeringControl theory (sociology)Electrical engineeringMathematicsControl (management)Physics

Abstract

fetched live from OpenAlex

This paper presents a new rotating transformation for the control of APLC (active power line conditioners). APLC is a power electronic inverter which is designed to suppress power line distortion caused by nonlinear loads. Existing control methods for the APLC such as the popular instantaneous power transformation, are based on measurements of both power line voltage and current to estimate the required compensation for the power line distortion. These methods are quite sensitive to the power line voltage distortion that can introduce control errors. This paper presents a new simple transformation method for the APLC which determines the correct power line compensation using the line current measurement only. This method simplifies the existing control processing and reduces the power line measurement requirements. The accuracy of the new method is not affected by the power line voltage distortion and therefore, it is reliable for all power line conditions. A 10 kVA prototype APLC has been developed to verify the accuracy and efficiency of the new method.

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: none
Teacher disagreement score0.959
Threshold uncertainty score0.864

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 head0.014
GPT teacher head0.239
Teacher spread0.225 · 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

Citations4
Published2000
Admission routes1
Has abstractyes

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