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Record W2536052462 · doi:10.1109/iecon.2008.4758055

Integrated three-leg VSC with a zig-zag transformer based three-phase four-wire DSTATCOM for power quality improvement

2008· article· en· W2536052462 on OpenAlexaff
Bhim Singh, P. Jayaprakash, T. R. Somayajulu, D. P. Kothari, Ambrish Chandra, Kamal Al‐Haddad

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Quality and Harmonics
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsDistribution transformerPower factorHarmonicsIsolation transformerAC powerEngineeringTransformerVoltage sourceThree-phaseElectronic engineeringDelta-wye transformerSwitched-mode power supplyEnergy efficient transformerElectric power systemControl theory (sociology)Electrical engineeringVoltageComputer sciencePower (physics)Physics

Abstract

fetched live from OpenAlex

In this paper, a new topology of DSTATCOM (Distribution Static Compensator) is proposed for power quality improvement in a three-phase four-wire distribution system. A three-leg VSC (Voltage Source Converter) based DSTATCOM is integrated with a zig-zag transformer for the compensation of reactive power for voltage regulation or for power factor correction along with load balancing, elimination of harmonics currents and neutral current compensation at the point of common coupling (PCC). The zig-zag transformer is used for providing a path to the zero sequence current in a three-phase four-wire distribution system. In order to reduce the voltage rating of the VSC, the zig-zag transformer is designed to have a third winding for integrating the DSTATCOM. This transformer connection provides the selection of ‘off the shelf’ VSC for this application and it also provides isolation for the power electronics system. The performance of the proposed system is validated through simulations using MATLAB software with its Simulink and Power System Blockset (PSB) toolboxes.

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 score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.063
GPT teacher head0.282
Teacher spread0.219 · 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

Citations23
Published2008
Admission routes1
Has abstractyes

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