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Record W2110673191 · doi:10.1109/pes.2009.5275728

Composite generation and transmission system adequacy assessment considering wind energy seasonal characteristics

2009· article· en· W2110673191 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 speedWind powerMonte Carlo methodReliability (semiconductor)Environmental scienceMeteorologySampling (signal processing)Transmission systemReliability engineeringTransmission (telecommunications)Scale (ratio)Electric power systemComputer scienceStatisticsEngineeringTelecommunicationsMathematicsPower (physics)Geography

Abstract

fetched live from OpenAlex

This paper examines the impact of seasonal changes in wind speed on the adequacy of composite generation and transmission systems with large-scale wind energy facilities. The relevant seasonal models are used to compare the system reliability indices obtained using annual models and seasonal models. The studies were conducted on the two test systems using a state sampling Monte Carlo approach. The studies presented illustrate the annual wind profile is an acceptable representation and that annual studies can be done directly using this profile. The procedures presented in this paper for creating seasonal/monthly wind energy conversion system models should be prove useful in situations where time period models are required to incorporate scheduled generation and transmission facility outages.

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 score0.947
Threshold uncertainty score0.485

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 head0.208
Teacher spread0.199 · 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

Citations6
Published2009
Admission routes1
Has abstractyes

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