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Record W2102137476 · doi:10.1109/tpwrd.2004.838640

Voltage Support by Distributed Static VAr Systems (SVS)

2005· article· en· W2102137476 on OpenAlexaff
Slaven Kincic, Xiaofeng Wan, D. McGillis, Ambrish Chandra, B.T. Ooi, F.D. Galiana, G. Joós

Bibliographic record

VenueIEEE Transactions on Power Delivery · 2005
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsMcGill UniversityResearch CanadaEricsson (Canada)École de Technologie SupérieureUniversité du Québec à Montréal
Fundersnot available
KeywordsVoltageTransformerAC powerReliability (semiconductor)Voltage regulationElectrical engineeringComputer scienceElectronic engineeringEngineeringTransmission systemTransmission (telecommunications)Control theory (sociology)Power (physics)Control (management)Physics

Abstract

fetched live from OpenAlex

This paper shows that when load centers require Static VAR Systems (SVS) for regulated voltage control, the strategy of using many, small, distributed SVS located at distribution buses is more advantageous than a few large bulk SVS located at the transmission or sub-transmission bus. The advantages are (i) standby to meet N-1 reliability criterion is reduced; (ii) costly high voltage transformers are no longer needed because the SVS can be connected directly to the low voltage distribution buses; (iii) distribution-side voltage support is more effective so that the total MVAr requirement of the distributed SVS is less. Simulation studies have demonstrated that the distributed SVS units operate harmoniously together.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

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 communication0.0010.001
Open science0.0010.000
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 head0.007
GPT teacher head0.196
Teacher spread0.190 · 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 designBench or experimental
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

Citations55
Published2005
Admission routes1
Has abstractyes

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