MétaCan
Menu
Back to cohort
Record W2536504613 · doi:10.1109/peds.2005.1619888

A 3-Phase 4-Wire Voltage Sag Compensator Based on Three Dimensions Space Vector

2006· article· en· W2536504613 on OpenAlexfundno aff
Kosol Oranpiroj, Suttichai Premrudeepreechacharn, Yuttana Kumsuwan, T. Boonsai, C.V. Nayar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Quality and Harmonics
Canadian institutionsnot available
FundersRoyal Golden Jubilee (RGJ) Ph.D. ProgrammeMinistère de la Santé et des Services sociaux
KeywordsVoltage sagControl theory (sociology)VoltageNonlinear systemSpace vectorThree-phaseCurrent (fluid)EngineeringComputer sciencePhysicsPower qualityElectrical engineeringPulse-width modulation

Abstract

fetched live from OpenAlex

Presently available voltage sag compensators are unable to handle neutral current caused by unbalanced and/or nonlinear loads or unbalanced source. In this paper, a 3-phase, 4-wire voltage sag compensator base on 3 dimensional voltage space vector is proposed which can handle the neutral current under voltage sag and nonlinear load conditions. A computer simulation model using PSIM has been developed to analyses the performance of the systems and its effectiveness to mitigate voltage sags

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)0.000
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

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)0.0030.001

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 head0.021
GPT teacher head0.247
Teacher spread0.226 · 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

Citations1
Published2006
Admission routes1
Has abstractyes

Explore more

Same topicPower Quality and HarmonicsFrench-language works237,207