MétaCan
Menu
Back to cohort
Record W2065605071 · doi:10.1109/tste.2011.2166415

Three-Phase Steady-State Model of Type-3 Wind Generation Unit—Part II: Model Validation and Applications

2011· article· en· W2065605071 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 Sustainable Energy · 2011
Typearticle
Languageen
FieldEngineering
TopicWind Turbine Control Systems
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSolverComputer scienceSteady state (chemistry)Frame (networking)Power system simulationWind powerAlgorithmSequence (biology)Flow (mathematics)Power (physics)Control theory (sociology)SimulationEngineeringElectric power systemMathematicsControl (management)Electrical engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

This paper presents the implementation and validation of the sequence-frame model of the Type-3 wind generation unit and the sequential sequence-frame power-flow solver (sequential-SFPS) algorithm, developed in the Part I of this paper. A set of case studies are reported to (1) validate the numerical accuracy of the developed model and the power-flow algorithm, (2) quantify the impact of the Type-3 control strategy on the steady-state three-phase power-flow solution, and (3) demonstrate the computational efficiency of the sequential-SFPS. Three test systems of different topologies, sizes, and parameters are examined. Where applicable, the results are validated based on comparison with the exact time-domain solution, using the PSCAD/EMTDC software tool.

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: none
Teacher disagreement score0.909
Threshold uncertainty score0.932

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.032
GPT teacher head0.226
Teacher spread0.194 · 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