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Record W1504479117 · doi:10.1002/9781118755525.ch18b

Real‐Time Simulation of Modular Multilevel Converters (MMCs)

2014· other· en· W1504479117 on OpenAlex
Luc Andre Gregoire, Jean Bélanger, Christian Dufour, Handy Fortin Blanchette, Kamal Al‐Haddad

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreOther

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".

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsOpal-Rt Technologies (Canada)École de Technologie Supérieure
Fundersnot available
KeywordsModular designConvertersReal-time simulationComputer scienceTopology (electrical circuits)Control engineeringSimulationEngineeringElectrical engineeringVoltageProgramming language

Abstract

fetched live from OpenAlex

In this chapter a thorough presentation of the modular multilevel converter MMC is made. Due to its particular construction, standard simulation methods cannot be used. Limitations of those methods are explained and more suitable control technics are proposed. The model can also be used for real-time simulation application. Issues raised by the converter topology are discussed in regard to the choice of hardware to achieve real-time simulation. Finally, examples of implementation for real-time application are given for the different technics previously discussed.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.343
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

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)0.0020.001

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 head0.007
GPT teacher head0.210
Teacher spread0.203 · 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

Quick stats

Citations6
Published2014
Admission routes1
Has abstractyes

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