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Record W1974580845 · doi:10.1109/tpwrd.2010.2060371

Damping Performance Analysis of IPFC and UPFC Controllers Using Validated Small-Signal Models

2010· article· en· W1974580845 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Power Delivery · 2010
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsManitoba HydroUniversity of Manitoba
Fundersnot available
KeywordsUnified power flow controllerControl theory (sociology)Flexible AC transmission systemController (irrigation)Electric power systemEngineeringElectric power transmissionControl engineeringSIGNAL (programming language)Benchmark (surveying)Electronic engineeringPower (physics)Power flowComputer scienceElectrical engineeringPhysics

Abstract

fetched live from OpenAlex

The paper discusses the dynamic behavior of two different flexible ac transmission system devices; the interline power-flow controller (IPFC) and the unified power-flow controller (UPFC) in a benchmark system. The small-signal model of the interline power-flow controller is developed and validated using detailed electromagnetic transients simulation. Using this validated model, the damping capabilities of the IPFC and the UPFC are compared and rationalized. From a small-signal dynamics point of view, it is shown that the series branches of these devices essentially segment the network creating a new structure. This structure change may be used to effectively improve system damping without requiring the design of a tuned feedback controller. The IPFCs two series branches in contrast to the UPFC's single series branch permit more opportunities for network segmentation. Hence, the IPFC has greater potential for improving the system's dynamic performance.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.498
Threshold uncertainty score0.714

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.205
Teacher spread0.186 · 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