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Record W1968983472 · doi:10.1109/tpwrs.2013.2264904

Utilization of the Area Risk Concept for Operational Reliability Evaluation of a Wind-Integrated Power System

2013· article· en· W1968983472 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 · 2013
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsWind powerReliability engineeringReliability (semiconductor)Electric power systemTurbineWind speedEngineeringPower (physics)Electrical engineeringMeteorologyAerospace engineering

Abstract

fetched live from OpenAlex

Wind power generation is significantly different from conventional thermal and hydro power generation in the sense that the wind power is governed by the atmosphere and cannot be dispatched like the conventional units in order to respond to the system requirements. The operational reliability of a conventional system depends on the failures of the committed units and the lead time of the next available unit. The reliability contribution of a wind turbine generator is mainly governed by the variability of wind speed at the wind site. A short-term wind model developed for the specific lead time should be suitably combined with the other committed units to evaluate the operational reliability of a power system with significant wind penetration. The area risk concept, previously developed to evaluate the reliability contribution of rapid start units and hot reserve units that are committed later in the lead time, is extended in this paper to incorporate wind power in evaluating the system reliability. The developed method is applied to the IEEE-RTS to evaluate the operational system well-being indices.

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 score0.853
Threshold uncertainty score0.681

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 head0.021
GPT teacher head0.233
Teacher spread0.212 · 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