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Record W2140812236 · doi:10.1109/tie.2010.2051392

An Online Control Algorithm for Application of a Hybrid ESS to a Wind–Diesel System

2010· article· en· W2140812236 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 Industrial Electronics · 2010
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsMcGill UniversityHydro-Québec
Fundersnot available
KeywordsDiesel fuelAutomotive engineeringController (irrigation)Wind powerComputer scienceFuel efficiencyLimitingEngineeringControl theory (sociology)Control engineeringControl (management)Electrical engineering

Abstract

fetched live from OpenAlex

Energy storage systems (ESSs) can be applied to mitigate some of the negative impacts associated with a variable power generation source such as wind energy. The control of ESS power must be accomplished over numerous time frames to meet system objectives and respect ESS capacity constraints. This paper proposes a two-level ESS control structure for use with a wind-diesel system, which is suitable for online implementation. The control is developed to coordinate power delivered from the two ESS levels in order to minimize diesel fuel consumption and limit up/down rates of the diesel plant. Different control modes are evaluated by simulation, and a subset of the results are validated using a hardware-in-the-loop representation. The controller that combines all three functionalities-minimizing dump load, limiting intrahour diesel ramp rates, and maximizing ESS utilization-demonstrates superior performance as measured by defined metrics and is proven to work online.

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: none
Teacher disagreement score0.968
Threshold uncertainty score0.783

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 head0.010
GPT teacher head0.219
Teacher spread0.209 · 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