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Record W2136136616

Risk based equivalent wind capacity in power generating systems

2004· article· en· W2136136616 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 International Conference on Probabilistic Methods Applied to Power Systems · 2004
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsWind powerTurbineGenerator (circuit theory)Automotive engineeringWind speedSteam turbineCapacity factorComputer scienceElectricity generationEngineeringPower (physics)Marine engineeringEnvironmental scienceElectrical engineeringMeteorologyMechanical engineeringPhysics
DOInot available

Abstract

fetched live from OpenAlex

Wind power is considered to be a promising and encouraging alternative for power generation because of its tremendous environmental and social benefits, together with public support and government incentives. The wind, however, is variable, site specific and an intermittent source of energy. The rated capacity of a wind turbine can be misleading if it is interpreted in the same way as that of a conventional generating unit. The actual wind turbine capacity is limited by the random variation of the wind speed and the turbine characteristics. As a result, it is difficult to assign a capacity credit to a wind turbine generator and most analyses simply look at the energy produced. This paper presents a technique used to determine the capacity contribution from a wind turbine generator using a risk based analysis of the overall system adequacy.

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)0.003
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.863
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.079
GPT teacher head0.316
Teacher spread0.238 · 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