MétaCan
Menu
Back to cohort
Record W1621895939 · doi:10.1109/pesgm.2015.7285676

Assessment of spare breaker requirements for high voltage transmission stations

2015· article· en· W1621895939 on OpenAlexaff
G. Hamoud

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsHydro One (Canada)
Fundersnot available
KeywordsSpare partCircuit breakerReliability engineeringProbabilistic logicComputer scienceTransformerElectric power systemMaintenance engineeringReliability (semiconductor)Failure rateEngineeringVoltagePower (physics)Electrical engineeringOperations management

Abstract

fetched live from OpenAlex

Summary form only given. This paper describes a probabilistic method based on a total risk index (probability times consequences) for assessing the number of spare breakers required for a group of similar high voltage breakers used in switching and transformer stations. The proposed method uses a Markov model for assessing the probability of failures and a bulk power system reliability program for evaluating failure consequences. The method considers a number of factors such as the group size, unit failure rate, unit repair time, transmission station layout, and other power system parameters that may impact the number of spare breakers. A cost/benefit analysis approach is used in determining the required number of spare breakers. The number of spare units is determined when the total cost (sum of spare unit costs, system operating costs and system outage costs due to breaker failures) is minimum. An example is given to illustrate the proposed method of assessment.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.001

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 head0.033
GPT teacher head0.291
Teacher spread0.258 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same topicPower System Reliability and MaintenanceFrench-language works237,207