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Record W2020721549 · doi:10.1109/tdc.2014.6863413

A review on energy management systems

2014· review· en· W2020721549 on OpenAlexaff
Haytham A. Mostafa, Ramadan El Shatshat, M.M.A. Salama

Bibliographic record

Venuenot available
Typereview
Languageen
FieldEngineering
TopicSmart Grid Energy Management
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsEnergy managementSmart gridComputer scienceContext (archaeology)Reliability (semiconductor)Work (physics)Energy consumptionEnergy storageReliability engineeringLoad managementEnergy management systemDemand responseEfficient energy useRisk analysis (engineering)Environmental economicsEnergy (signal processing)ElectricityEngineeringBusinessElectrical engineering

Abstract

fetched live from OpenAlex

In the context of implementing the smart grid, electric energy consumption, generation resources, energy storage, plug-in electric vehicles, should be managed and optimized in a way that saves energy, improves efficiency, enhance reliability and maintain security while meeting the increasing demand at minimum operating cost. As a consequence, energy management systems are receiving more attention from the researchers and utilities. Accordingly, the main concern of this work is to investigate different energy management systems whether owned by a customer or by the distribution system utility.

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 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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.560
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.025
GPT teacher head0.254
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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations18
Published2014
Admission routes1
Has abstractyes

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