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Record W2018637318 · doi:10.1109/icc.2013.6655612

Advanced scheduling protocol for electric vehicle home charging with time-of-use pricing

2013· preprint· en· W2018637318 on OpenAlexaff
Dhaou Said, Soumaya Cherkaoui, Lyes Khoukhi

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicElectric Vehicles and Infrastructure
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsComputer scienceScheduling (production processes)Electric vehicleAutomotive engineeringComputer networkDistributed computingMathematical optimizationEngineeringPower (physics)Mathematics

Abstract

fetched live from OpenAlex

In this paper, a scheduling protocol for electric vehicle (EV) home charging with time of use pricing is introduced. This work addresses the problem of EVs charging at home by adopting an appropriate charging process protocol over Power Line Communications (PLC). The scheduling protocol is aimed at minimizing peak loads on distribution feeders due to multiple EVs charging while using a time-of-use pricing policy. Energy efficiency and performance are both taken into account. An appropriate analytical formulation of the scheduling problem is given together with the proposed scheduling protocol. Simulations demonstrate the effectiveness of the proposed approach in minimizing peak loads while satisfying the defined constraints.

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)
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 score0.266
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.229
Teacher spread0.221 · 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 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

Citations21
Published2013
Admission routes1
Has abstractyes

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