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Record W2160957068 · doi:10.1109/tpwrd.2003.813888

DC overvoltage control during loss of converter in multiterminal voltage-source converter-based HVDC (M-VSC-HVDC)

2003· article· en· W2160957068 on OpenAlexaff
Weixing Lu, Boon‐Teck Ooi

Bibliographic record

VenueIEEE Transactions on Power Delivery · 2003
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsMcGill University
Fundersnot available
KeywordsConvertersOvervoltageVoltage sourceElectrical engineeringController (irrigation)EngineeringVoltageElectric power systemPower (physics)HVDC converter stationHVDC converterElectronic engineeringPhysics

Abstract

fetched live from OpenAlex

Security requires that a system continues to function even when any one subsystem fails. A multiterminal HVDC system consists of N voltage-source converters (VSCs) exchanging power through a DC network. When any one converter is lost, before the surviving (N-1) converters have time to re-establish a new power balance, the excess DC power can produce voltage spikes which are destructive to the power electronic switches. The paper shows that the advanced DC voltage controller (ADCVC), which is a higher hierarchical controller, can meet the targeted voltage margin.

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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.192
Teacher spread0.186 · 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

Citations115
Published2003
Admission routes1
Has abstractyes

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