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Record W2063868897 · doi:10.1109/pesgm.2012.6345610

Dynamic performance of average-value models for multi-terminal VSC-HVDC systems

2012· article· en· W2063868897 on OpenAlex

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
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsConvertersVoltage sourceComputer scienceElectric power systemTransient (computer programming)Electronic engineeringTerminal (telecommunication)Control engineeringPower (physics)EngineeringVoltageElectrical engineeringTelecommunications

Abstract

fetched live from OpenAlex

Voltage Source Converter (VSC) HVDC technologies present a bright opportunity in a variety of fields within the power system industry due to their recognized advantages in comparison to conventional line-commutated HVDC systems. Computational burden introduced by detailed modeling of VSC-HVDC systems in EMT-type programs complicates the study of transient events. Detailed modeling includes the representation of semiconductor switches and causes significant deterioration in computational speed. This paper presents the concept of average-value modeling applied to two- and three-level VSC-HVDC systems. The modeling approach is validated for a multi-terminal VSC-based HVDC system used to integrate off-shore wind generation. Dynamic performance simulation results using average-value models are compared against detailed model results. Some results are also presented for MMC converters.

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.

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 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 score0.485
Threshold uncertainty score0.418

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)0.0000.000

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 head0.023
GPT teacher head0.249
Teacher spread0.226 · 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

Citations63
Published2012
Admission routes1
Has abstractyes

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