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Record W2059411722 · doi:10.1049/iet-rpg.2009.0070

Reliability assessment of a wind-power system with integrated energy storage

2010· article· en· W2059411722 on OpenAlexaff
Faruk A. Bhuiyan, Amirnaser Yazdani

Bibliographic record

VenueIET Renewable Power Generation · 2010
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsWestern University
Fundersnot available
KeywordsReliability engineeringReliability (semiconductor)Wind powerElectric power systemMATLABComputer scienceBattery (electricity)Energy storagePower (physics)Automotive engineeringEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

This study looks into reliability assessment and components rating of a wind-power system with integrated battery energy storage. The system can potentially be used in remote electrification projects to mitigate the reliance on diesel generators. A reliability assessment method has been proposed in this study, based on a combination of the traditional analytical and simulation-based approaches, to enable calculation of reliability indices, required battery capacity and power rating, and power rating of the power-electronic converter of the wind-power units. The proposed method is easy to implement in the MATLAB software environment, takes into account the units forced outage rate (FOR), and also permits modelling of the grid-connected mode.

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)0.001
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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

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 head0.005
GPT teacher head0.200
Teacher spread0.195 · 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

Citations85
Published2010
Admission routes1
Has abstractyes

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