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Record W1785722747 · doi:10.1109/pes.2005.1489156

A nonlinear control approach to increase power oscillations damping by means of the SSSC

2005· article· en· W1785722747 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 Power Engineering Society General Meeting, 2005 · 2005
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsQueen's University
Fundersnot available
KeywordsControl theory (sociology)Nonlinear systemCapacitorAffine transformationLinearizationFeedback linearizationController (irrigation)Multivariable calculusComputer scienceVoltageControl engineeringMathematicsEngineeringPhysicsControl (management)

Abstract

fetched live from OpenAlex

Static series synchronous compensators (SSSC) have recently found applications in power oscillation damping (POD) improvement. Nonlinear dynamics associated with the SSSC's dc-link capacitor voltage, and effective interactions among its variables validate the use of nonlinear and multi-variable modeling and control techniques. A novel nonlinear input-affine multivariable model for a series connected SSSC with the transmission line is developed and formulated in this paper. Developing an affine model is a critical step in the design and implementation of many nonlinear and robust control approaches. Based on the proposed affine model, a feedback linearization nonlinear controller is introduced and used to improve the POD. Simulation results validate the feasibility of the proposed modeling and control approaches in maintaining the dc side capacitor voltage constant while effectively damp out power system oscillations. In addition, the zero dynamics of the system remains stable which means no deviation will occur in uncontrolled state variables.

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)0.001
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 score0.651
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.191
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