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Record W2154980236 · doi:10.1109/pes.2006.1708944

The hybrid power flow controller - a new concept for flexible AC transmission

2006· article· en· W2154980236 on OpenAlexaff
J. Bebic, Peter W. Lehn, Mohammad Reza Iravani

Bibliographic record

Venue2006 IEEE Power Engineering Society General Meeting · 2006
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsConvertersShunt (medical)Network topologyTopology (electrical circuits)AC powerControl theory (sociology)Computer scienceVoltage sourceVoltageElectronic engineeringEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

In this paper, two such topologies are presented. The first one consists of a shunt connected controllable source of reactive power, and two series connected voltage-sourced converters - one on each side of the shunt device. The second topology is a dual of the first; it is based on two shunt connected current-sourced converters around a series connected reactive compensator. In both cases the converters can exchange active power through a common DC circuit. Since both topologies make use of converters in addition to the (presumably existing) passive components, they can be regarded as hybrid, and the resulting FACTS controllers are thus named "hybrid power flow controllers", or HPFC. The analysis carried out that the HPFC offers performance characteristics similar to those of the UPFC. This paper presents some of the results. The rest of this paper is organized as follows. The HPFC topology that employs series VSCs is introduced. The steady state analysis is given and operating characteristics are derived. The dual topology, based on shunt connected current-sourced converters is presented

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

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 studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
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 head0.005
GPT teacher head0.195
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 designTheoretical or conceptual
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

Citations28
Published2006
Admission routes1
Has abstractyes

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