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Record W2024825567 · doi:10.1109/tpwrs.2012.2205022

Adequacy Assessment Considerations in Wind Integrated Power Systems

2012· article· en· W2024825567 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 Power Systems · 2012
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsBC Hydro (Canada)Manitoba HydroUniversity of Saskatchewan
Fundersnot available
KeywordsWind powerElectric power systemReliability engineeringElectricity generationWind speedEngineeringElectric power transmissionRange (aeronautics)Computer sciencePower (physics)Electrical engineeringMeteorologyAerospace engineering

Abstract

fetched live from OpenAlex

There is a wide range of possible data representations, models and solution techniques available when conducting adequacy assessments of wind integrated generation or composite generation and transmission systems. This paper presents some of the basic factors and procedures that need to be considered when conducting wind integrated system adequacy assessment. Focus is placed on possible wind speed data models, wind energy conversion system models and their application in generation and bulk system adequacy evaluation. A series of studies is presented using two published test systems, the RBTS and the IEEE-RTS. These studies illustrate the effects of wind farm correlation on the determination of wind power capacity credit indices and on general adequacy assessment in generating and bulk electric systems. The impacts on the system well-being indices of adding wind power to a bulk electric system and the effects on the adequacy of a wind integrated system from energy storage obtained using hydro generation are examined by application to the IEEE-RTS.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.962
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.238
Teacher spread0.223 · 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