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Record W2114661994 · doi:10.1109/tec.2004.827718

Generating Capacity Adequacy Associated With Wind Energy

2004· article· en· W2114661994 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 Energy Conversion · 2004
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsWind powerWind speedReliability (semiconductor)Monte Carlo methodRange (aeronautics)Electricity generationReliability engineeringEnergy (signal processing)Computer scienceEnvironmental scienceEngineeringPower (physics)MeteorologyStatisticsElectrical engineeringMathematicsAerospace engineering

Abstract

fetched live from OpenAlex

The wind is a highly variable energy source and behaves far differently than conventional energy sources. This paper presents a methodology for capacity adequacy evaluation of power systems including wind energy. The results and discussions on two representative systems containing both conventional generation units and wind energy conversion systems (WECS) are presented. A Monte Carlo simulation approach is used to conduct the analysis. The hourly wind speeds are simulated using an autoregressive moving average time-series model. A wide range of studies were conducted on two different sized reliability test systems. The studies show that the contribution of a WECS to the reliability performance of a generation system can be quantified and is highly dependent on the wind site conditions. A WECS can make a significant reliability contribution given a reasonably high wind speed. Wind energy independence also has a significant positive impact on the reliability contribution of multiple WECS.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.831
Threshold uncertainty score0.843

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 head0.009
GPT teacher head0.171
Teacher spread0.163 · 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