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Record W2082051679 · doi:10.1002/etep.154

Incorporating multi‐state unit models in composite system adequacy assessment

2007· article· en· W2082051679 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

VenueEuropean Transactions on Electrical Power · 2007
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsDeratingReliability engineeringReliability (semiconductor)StatisticContingencyState (computer science)Computer scienceEngineeringStatisticsMathematicsPower (physics)Electrical engineeringVoltageAlgorithm

Abstract

fetched live from OpenAlex

Abstract Components are usually represented by a two state model in conventional generating capacity and composite generation and transmission system reliability studies. Multi‐state generating unit models create a significant increase in the number of generation contingency states and can result in a considerable increase in the overall solution time. In order to avoid this problem, the derated states are usually amalgamated with the totally forced out state to create the derating‐adjusted forced outage rate (DAFOR). This statistic is also known as the equivalent forced outage rate (EFOR). Studies have shown that modeling large generating units in generating capacity adequacy assessments using DAFOR can provide pessimistic appraisals. Many utilities therefore use multi‐state generating unit representations to assess generating capacity adequacy, in order to obtain more accurate appraisals. There is relatively little published material dealing with the effects of using multi‐state generating unit representations in composite system adequacy assessment. This paper illustrates these effects by application to the IEEE‐Reliability Test System (RTS). Load point and system indices for the test system are presented to illustrate the impact of incorporating multi‐state representations in composite system adequacy assessment. Attention is focused on the effects of model variations including how many derated states should be used in a multi‐state model to obtain a reasonably accurate appraisal. Copyright © 2007 John Wiley & Sons, Ltd.

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 score0.966
Threshold uncertainty score0.970

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.015
GPT teacher head0.235
Teacher spread0.221 · 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