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Record W2143109034 · doi:10.1109/tia.2009.2031897

Influence of Subsea Cables on Offshore Power Distribution Systems

2009· article· en· W2143109034 on OpenAlexaff
Xiaodong Liang, W.M. Jackson

Bibliographic record

VenueIEEE Transactions on Industry Applications · 2009
Typearticle
Languageen
FieldEngineering
TopicPower Quality and Harmonics
Canadian institutionsSchlumberger (Canada)
Fundersnot available
KeywordsSubseaSubmarine pipelineHarmonicsHarmonicPower (physics)Marine engineeringEngineeringHarmonic analysisResonance (particle physics)Electric power systemElectrical engineeringComputer scienceElectronic engineeringAcousticsPhysicsVoltageGeotechnical engineering

Abstract

fetched live from OpenAlex

Subsea cable applications for the offshore power distribution systems create technical challenges in the system design, operation, and maintenance. Harmonic parallel resonance introduced by subsea cables is one of the main concerns. In this paper, parallel resonance is investigated for an offshore distribution system with lengthy subsea cables on four interconnected platforms. Variable frequency drives (VFDs) are the dominant loads on the platforms, which make up to 98% of the total load demands. Subsea cables create a complicated parallel resonance condition in the system. Several resonant frequency bands could interact with harmonic currents injected by VFDs. The ways to attenuate resonance and mitigate harmonics are discussed and compared. An optimized solution for harmonic mitigation is proposed for the system.

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)0.001
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: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.017
GPT teacher head0.247
Teacher spread0.231 · 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

Citations13
Published2009
Admission routes1
Has abstractyes

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