MétaCan
Menu
Back to cohort
Record W2169586111 · doi:10.1109/pes.2009.5275595

Power system stabilizers in variable speed wind farms

2009· article· en· W2169586111 on OpenAlexaff
Carlos Pérez Martı́nez, G. Joós, B.T. Ooi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsMcGill University
Fundersnot available
KeywordsElectric power systemControl theory (sociology)Wind powerWind speedRotational speedController (irrigation)Power (physics)Rotor (electric)EngineeringStabilizer (aeronautics)Variable (mathematics)AC powerBandwidth (computing)Computer scienceElectrical engineeringVoltageControl (management)TelecommunicationsPhysicsAerospace engineeringMathematics

Abstract

fetched live from OpenAlex

Synchronous generators in a power system exhibit rotor oscillations around their nominal steady state rotational speed. Conventional power system stabilizers have limited damping capability of inter-area mode of oscillations, when the frequencies lie beyond their bandwidth. Variable speed wind generators, with fast real and reactive power regulation capabilities, are being integrated into power systems. This paper investigates different power system stabilizer designs and damping strategies suitable for variable speed wind farm applications. Based on damping applications with flexible AC transmission system (FACTS) and HVDC, the paper investigates how power system stabilizer functions can be integrated into the wind farm controller and their effectiveness. Testing scenarios include different locations of wind farm.

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)0.001
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.190
Teacher spread0.185 · 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

Citations25
Published2009
Admission routes1
Has abstractyes

Explore more

Same topicPower System Optimization and StabilityFrench-language works237,207