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Record W2112943655 · doi:10.1109/ccece.2005.1556988

Wind power simulation model for reliability evaluation

2006· article· en· W2112943655 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsWind powerWind speedReliability (semiconductor)Reliability engineeringElectric power systemComputer sciencePower (physics)Wind power forecastingMarine engineeringMeteorologyEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

The rapidly increasing contribution of wind power to electric power generation around the world has motivated a need to develop more widely applicable methodologies for evaluating the actual benefits of adding wind turbines to traditional power generating systems. Reliability and cost evaluation of wind generation systems requires simulation of long-term chronological wind speed data for specified geographical wind farm sites. The main steps to construct the wind speed simulation model are presented in this paper. It is important that the developed models maintain the main statistical characteristics of the wind farm locations. Wind speed data from two wind sites are used to illustrate the model. The results of wind data simulation, power output profile, and power system risk evaluation are presented and compared using different types of wind models at different wind farm sites. The objective is to derive a general and appropriate model for reliability evaluation of power systems containing wind sources

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 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 score0.867
Threshold uncertainty score0.317

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.018
GPT teacher head0.257
Teacher spread0.240 · 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

Quick stats

Citations59
Published2006
Admission routes1
Has abstractyes

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