MétaCan
Menu
Back to cohort
Record W2168492352 · doi:10.1109/tpwrs.2008.2004840

A Stochastic Optimization Approach to Rating of Energy Storage Systems in Wind-Diesel Isolated Grids

2008· article· en· W2168492352 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 Transactions on Power Systems · 2008
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsMcGill University
Fundersnot available
KeywordsSizingDiesel fuelWind powerEnergy storageAutomotive engineeringStochastic optimizationEngineeringOperating costComputer scienceEnvironmental scienceWaste managementMathematical optimizationElectrical engineeringPower (physics)

Abstract

fetched live from OpenAlex

Wind-diesel systems represent a proactive step towards sustainable remote communities. However, for high ratios of wind energy, the necessity of a dump load and the diesel operating constraints need to be considered. Energy storage systems offer a means of optimizing energy use and further reducing consumption of diesel fuel. This paper proposes a methodology for storage sizing based on stochastic optimization. The problem is formulated and solved using representative data. The dependence of storage sizing and the cost of delivered energy on wind penetration levels, storage efficiency, and diesel operating strategies are considered. Results demonstrate that for high wind penetration, the availability of storage, together with an appropriate diesel operating approach, can result in significant cost savings in terms of fuel and operating costs.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.995
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.008
GPT teacher head0.177
Teacher spread0.169 · 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