MétaCan
Menu
Back to cohort
Record W2090052210 · doi:10.1243/1748006xjrr218

Reliability assessment of a wind power delivery system

2008· article· en· W2090052210 on OpenAlexaff
Rajesh Karki, Jason Patel

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability · 2008
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsWind powerElectric power systemRenewable energyReliability engineeringSizingElectric power transmissionTransmission lineTransmission (telecommunications)Reliability (semiconductor)Transmission systemPower system simulator for engineeringEngineeringComputer scienceAutomotive engineeringPower (physics)Electrical engineering

Abstract

fetched live from OpenAlex

Growing environmental concerns have led to renewable energy policies, such as the renewable portfolio standard, that have set ambitious targets for wind power penetration in electric power systems throughout the world. In many cases, the geographical locations with good wind resources are not close to the main load centres. Wind is a highly variable energy source and, therefore, transmission system planning for wind delivery is very different from conventional transmission planning. It becomes extremely important to assess the availability of wind power against the cost of transmission facility connecting to the power grid. This paper presents an analytical method to determine appropriate transmission line sizing based on its contribution to the overall system risk. The studies can also be used to evaluate the reliability contribution of the combined wind generation and transmission systems. The effects of generation, transmission, and load parameters on risk-based transmission line sizing are presented using a test system. The methodology and results presented in this paper should be useful in wind site selection and transmission system planning for delivering wind power.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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

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 head0.006
GPT teacher head0.199
Teacher spread0.192 · 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 designSimulation or modeling
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

Citations18
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Institution of Mechanical Engineers Part O Journal of Risk and ReliabilitySame topicPower System Reliability and MaintenanceFrench-language works237,207