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Record W2032745449 · doi:10.1109/pedg.2014.6878653

A new solid-state HVDC circuit breaker topology for offshore wind farms

2014· article· en· W2032745449 on OpenAlexaff
Shahram Negari, Dewei Xu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCircuit breakerOffshore wind powerEngineeringElectrical engineeringFault (geology)ConvertersElectric power transmissionWind powerGridSurge arresterTopology (electrical circuits)Computer scienceVoltage

Abstract

fetched live from OpenAlex

This paper presents a new topology for solid-state HVDC circuit breakers which does not require MOV for fault energy absorption. Due to its simple yet robust design, it offers a reliable and cost effective solution for isolating faults in HVDC lines connecting remote generating stations to the grid. Since the proposed design does not contain a mechanical breaker or a metal-oxide varistor (MOV), problems resulting from wear and tear of moving parts, arc faults, and degradation or catastrophic failure of surge arrestors are entirely eliminated. This design has inherently a very fast response and is particularly suitable for voltage source converters that are vulnerable against dc faults. To verify the performance and dependability of the proposed circuit breaker, a computer simulation has been developed to handle faults occurring at a 300 kV submarine transmission line that connects a typical 250 MW offshore wind farm to the grid.

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 score0.004
Threshold uncertainty score0.013

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.012
GPT teacher head0.232
Teacher spread0.221 · 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

Citations19
Published2014
Admission routes1
Has abstractyes

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