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Record W2156410944 · doi:10.1109/tpwrd.2008.923153

EMTP Simulation of a Chain-Link STATCOM

2008· article· en· W2156410944 on OpenAlexaff
Nikunj M. Shah, Vijay K. Sood, V. Ramachandran

Bibliographic record

VenueIEEE Transactions on Power Delivery · 2008
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsConcordia University
Fundersnot available
KeywordsEmtpThyristorPulse-width modulationConvertersCapacitorTransient (computer programming)VoltageControl theory (sociology)Voltage sourceEngineeringTopology (electrical circuits)Three-phaseElectronic engineeringElectrical engineeringComputer scienceElectric power systemPhysicsPower (physics)

Abstract

fetched live from OpenAlex

A recent addition to the STATCOM family has been obtained by connecting a number of gate turn off (GTO) thyristor converters in series on the ac side of the system. Each GTO converter forms one ldquolinkrdquo of a one-phase, full-bridge voltage-source converter (VSC) and is referred to as a ldquochain link converterrdquo (CLC). Each GTO of the CLC is switched ldquoon/offrdquo only once per cycle of the fundamental frequency by employing a sinusoidal pulse width modulation (SPWM) technique. Approximate models of a three-phase chain link STATCOM (CLS) usingdq-transformation are derived to design two controllers for controlling both reactive current and ac voltage to stabilize the system voltage at the point of common coupling. A novel technique, called the rotated gate signal pattern, is used for balancing the voltages of the link dc capacitors of the VSC. The performance investigation of the CLS system when used in a radial line transmission system is carried out under steady- and transient-state operating conditions by means of the simulation package electromagnetic transients program-restructured version.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.214
Teacher spread0.193 · 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

Citations5
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Transactions on Power DeliverySame topicMultilevel Inverters and ConvertersFrench-language works237,207