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A BESS control system for reducing fuel-consumption and maintenance costs of diesel-hybrid mini-grids with high penetration of renewables

2013· article· en· W2155538189 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsConcordia University
Fundersnot available
KeywordsAutomotive engineeringRenewable energyDiesel fuelMicrogridGridWind powerEnergy storagePhotovoltaicsElectric power systemPhotovoltaic systemComputer scienceFuel efficiencyEnvironmental scienceEngineeringPower (physics)Electrical engineering

Abstract

fetched live from OpenAlex

Diesel hybrid mini-grids with high penetration of renewables have the potential for reduced operation costs and environmental impacts. However, the fluctuating characteristics of wind and Photovoltaics (PV) and the large variations of the frequently unbalanced mini-grid loads, result in additional challenges for optimizing the operation of the diesel genset(s). In such a case, a Battery Energy Storage System (BESS) can be very beneficial. This paper presents a control system of a BESS that allows it to operate in multiple modes. In the genset support mode, it balances the load, compensates for reactive power and forces the genset(s) to operate in a desired power range. In the grid forming mode, it supplies balanced voltages to highly unbalanced loads. Simulation results are provided.

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 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 score0.266
Threshold uncertainty score0.353

Codex and Gemma teacher scores by category

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

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 head0.004
GPT teacher head0.167
Teacher spread0.163 · 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

Quick stats

Citations15
Published2013
Admission routes1
Has abstractyes

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