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Record W2023334666 · doi:10.1002/etep.198

Improvement of transient stability by unified power flow controller based on Hamiltonian system theory

2007· article· en· W2023334666 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

VenueEuropean Transactions on Electrical Power · 2007
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsUniversity of Alberta
FundersUniversity of Hong Kong
KeywordsUnified power flow controllerControl theory (sociology)Electric power systemHamiltonian systemHamiltonian (control theory)Power flowComputer scienceController (irrigation)Control engineeringMathematicsEngineeringPower (physics)PhysicsControl (management)Mathematical optimizationArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract In this paper we propose a novel Hamiltonian theory based controller design methodology for unified power flow controller (UPFC) control to improve the dynamic performance of power systems. The Hamiltonian theory of the differential‐algebraic (DA) system is described and a simple control strategy is deduced to stabilize the system. Furthermore, the influence of the control law on the stability region of the system is discussed as well. It can be proved that the stability region of the system can indeed be enlarged under the control strategy. The UPFC control scheme of multi‐machine power system is developed, and a classical three‐generator system is used to validate the effectiveness of the control law. Copyright © 2007 John Wiley & Sons, Ltd.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.005
GPT teacher head0.182
Teacher spread0.177 · 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