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Record W4253507867 · doi:10.1109/pesc.1994.373873

Three phase series VAr compensation based on a voltage controlled current source inverter with supplemental modulation index control

2002· article· en· W4253507867 on OpenAlexaff
G. Joos, J. Espinoza

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicPower Systems and Renewable Energy
Canadian institutionsConcordia University
Fundersnot available
KeywordsModulation indexControl theory (sociology)Pulse-width modulationTotal harmonic distortionInverterAC powerPower factorTransformerComputer scienceVoltageVoltage sourceElectronic engineeringEngineeringControl (management)Electrical engineering

Abstract

fetched live from OpenAlex

Shunt type static VAr compensators are an effective means of increasing the transmission capability of power systems and of increasing the power factor of industrial loads. This paper presents an alternative in the form of a series-connected transformer coupled PWM inverter. The scheme consists of a current source inverter connected to a self controlled DC bus. It presents the following features: (a) instantaneous series injected voltage control through online modulation index control; and (b) steady state modulation index control to a value near unity. The first feature results in fast dynamic response, while the second feature ensures that the harmonic distortion of the injected voltage under steady state operation is kept to a minimum, independently of the operating conditions. Operation of the compensator and of the two loop control scheme are presented. Simulation and experimental results on a prototype unit confirm the feasibility of the proposed structure.>

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.014
GPT teacher head0.223
Teacher spread0.209 · 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 designBench or experimental
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
Published2002
Admission routes1
Has abstractyes

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