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Record W2100829286 · doi:10.1109/pesw.2000.847348

Multi-teriminal UPFC for power system deregulation

2002· article· en· W2100829286 on OpenAlexaff
B. Mwinywiwa, Bin Lu, B.T. Ooi, F.D. Galiana, D. McGillis, R.J. Marceau, G. Joós

Bibliographic record

Venue2000 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.00CH37077) · 2002
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsConcordia UniversityPolytechnique MontréalMcGill University
Fundersnot available
KeywordsUnified power flow controllerElectric power transmissionConvertersElectric power systemFlexible AC transmission systemTransmission lineComputer scienceController (irrigation)Transmission systemPower (physics)Power transmissionLine (geometry)Control theory (sociology)VoltageTransmission (telecommunications)EngineeringControl (management)Power flowElectrical engineeringTelecommunicationsPhysicsMathematics

Abstract

fetched live from OpenAlex

One original purpose of FACTS controllers is to increase the transmission capacity of existing lines thus deferring the necessity of building new lines. FACTS, such as the unified power flow controller (UPFC), have also been regarded as controllers for routing power in the market-driven, deregulated power systems. Hitherto, the UPFC has been conceived to control the complex powers through a radial line. This paper presents the concept of a multi-terminal UPFC (M-UPFC), which serves to control the complex powers of several transmission lines converging towards (or radiating from) a transmission node. In order to show that a M-UPFC can be built, that it has stable operation and that it has all the control degrees of freedom of UPFCs, a laboratory model based on 3 units of 3-phase, voltage-source converters has been assembled and tested.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

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)0.0020.000

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 head0.204
Teacher spread0.187 · 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

Citations7
Published2002
Admission routes1
Has abstractyes

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Same venue2000 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.00CH37077)Same topicPower System Optimization and StabilityFrench-language works237,207