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Record W2144182143 · doi:10.1109/pes.2007.385621

Determination of Substation Models for Composite System Reliability Evaluation

2007· article· en· W2144182143 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 Power Engineering Society General Meeting · 2007
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsUniversity of ManitobaManitoba Hydro
Fundersnot available
KeywordsReliability engineeringReliability (semiconductor)Monte Carlo methodComputer scienceTransmission systemGridTransmission (telecommunications)EngineeringPower (physics)

Abstract

fetched live from OpenAlex

The reliability performance of transmission system substations is critical for overall system reliability. Failure events at main grid substations can lead to multiple outages with possible cascading consequences and widespread loss of customer load. Considerable knowledge on substation reliability analysis has been gained from the application of primarily analytical methods. The complexity, however, of substation switching operations does not lend itself to pure analytical treatment. Simulation methods are more suitable as the mathematical modeling of the relationship between events and outcomes is not always possible. The paper expands the existing methodology and describes a method to perform reliability evaluation of substation switching arrangements based on the sequential Monte Carlo simulation. The method is applied in the reliability analysis and comparison of the most commonly used substation switching configurations. The paper shows how the results of the analysis can be applied to model substations in a composite system reliability evaluation.

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)0.004
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 score0.518
Threshold uncertainty score0.950

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
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 head0.013
GPT teacher head0.240
Teacher spread0.227 · 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