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Record W2133068933 · doi:10.1109/pes.2006.1709337

Estimation of wind penetration as limited by frequency deviation

2006· article· en· W2133068933 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

Venue2006 IEEE Power Engineering Society General Meeting · 2006
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsMcGill University
Fundersnot available
KeywordsWind powerPenetration (warfare)Frequency deviationWind speedEnvironmental scienceStandard deviationThermalThermal power stationMeteorologyControl theory (sociology)Marine engineeringComputer scienceEngineeringElectrical engineeringPhysicsMathematicsAutomatic frequency controlStatistics

Abstract

fetched live from OpenAlex

Wind power fluctuations cause frequency deviation from the 60 Hz standard. Using the composite frequency response of a small system of thermal power plants, it is estimated that power fluctuation of 5% of the total thermal plant capacity can be tolerated without exceeding 1% frequency deviation. The technology to filter out the power fluctuations in the wind farms already exists to increase wind power penetration. But perfect filtering sacrifices as much as 27.6% of the wind power which otherwise can be acquired. The paper presents a method of quantifying wind penetration based on the amount of fluctuating power which can be filtered by the wind farms and the thermal plants. For optimal wind power acquisition, the penetration level is estimated to be 49%.

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 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: Empirical
Teacher disagreement score0.148
Threshold uncertainty score1.000

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 head0.003
GPT teacher head0.181
Teacher spread0.178 · 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