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Record W1821888196

Reliability Cost/Worth Associated With Wind Energy and Energy Storage Utilization in Electric Power Systems

2008· article· en· W1821888196 on OpenAlexaff
Bagen Bagen, R. Billinton

Bibliographic record

VenueProceedings of the 10th International Conference on Probablistic Methods Applied to Power Systems · 2008
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsUniversity of SaskatchewanManitoba Hydro
Fundersnot available
KeywordsReliability engineeringWind powerReliability (semiconductor)Energy storageIntermittent energy sourceElectric power systemEnergy (signal processing)Computer scienceRenewable energyPower (physics)EngineeringDistributed generationElectrical engineering
DOInot available

Abstract

fetched live from OpenAlex

Wind is being recognized as an encouraging and cost effective generation source both in large grid connected systems and small isolated applications. The actual benefits obtained from utilizing wind energy for electric power generation can be investigated using reliability and economic evaluation techniques. The focus of these techniques is usually directed to the areas of reliability and the investment/operation alternatives associated with determining a desired reliability level. Considerable effort has been devoted to the reliability evaluation of power systems utilizing wind energy. Comparatively less emphasis has been given to the related economic analyses of such systems particularly considering possible energy storage capability. This paper presents a reliability cost/worth evaluation method that can incorporate the impacts of wind energy and energy storage utilization in electric power systems.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
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 head0.035
GPT teacher head0.264
Teacher spread0.229 · 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

Citations23
Published2008
Admission routes1
Has abstractyes

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