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Record W2080653378 · doi:10.1049/iet-gtd.2012.0266

Approximate model and low‐order harmonic reduction for high‐voltage direct current tap based on series single‐phase modular multilevel converter

2013· article· en· W2080653378 on OpenAlexaff
Quanrui Hao, Guojie Li, Boon‐Teck Ooi

Bibliographic record

VenueIET Generation Transmission & Distribution · 2013
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsMcGill University
Fundersnot available
KeywordsModular designReduction (mathematics)Series (stratigraphy)HarmonicVoltageCurrent (fluid)Control theory (sociology)Three-phaseComputer sciencePhase (matter)Total harmonic distortionLow voltageVoltage reductionElectronic engineeringMathematicsEngineeringElectrical engineeringPhysicsControl (management)Artificial intelligence

Abstract

fetched live from OpenAlex

The series single‐phase modular multilevel converter (SSP–MMC) is investigated as one option for high‐voltage direct current tap aimed to reduce the number of switching devices by one‐third. First an approximation method is applied to calculate the sub‐module capacitor voltage of the proposed SSP–MMC. Based on that, the approximate equivalent circuits for ac and dc sides are both presented to demonstrate the mechanism of the second and third harmonics. Then the methods to reduce the second and third harmonics are proposed as parts of the overall control loop. Simulation results obtained in power system computer aided design (PSCAD) are provided to validate the brief equivalent models and the second and third harmonic reduction methods.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.022
GPT teacher head0.237
Teacher spread0.215 · 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

Citations35
Published2013
Admission routes1
Has abstractyes

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