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Record W3007319410 · doi:10.1109/access.2020.2974477

Decentralized Game-Theoretic Scheme for D-EVSE Based on Renewable Energy in Smart Cities: A Realistic Scenario

2020· article· en· W3007319410 on OpenAlexafffund
Turki G. Alghamdi, Hussein T. Mouftah

Bibliographic record

VenueIEEE Access · 2020
Typearticle
Languageen
FieldEngineering
TopicElectric Vehicles and Infrastructure
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsRenewable energyComputer scienceTestbedSmart gridGame theoryGridPhotovoltaic systemScheme (mathematics)Distributed computingEngineeringElectrical engineeringComputer network

Abstract

fetched live from OpenAlex

In this paper, we address a decentralized power production and management system based on Game Theory (GT) for Electric Vehicles' (EVs') interplay with a Decentralized Electric Vehicle Supply Equipment (D-EVSE) located at the public supply station. Renewable energy production such as solar energy (PV) is considered as the main power source for our D-EVSE and we consider the connection to the grid when the solar renewable energy system is failing to respond to the demand. We propose a decentralized GT (D-GT) scheme aiming to optimize the EVs' interaction with the D-EVSE considering both EVs' satisfaction as well as the D-EVSEs' stability. Also, the D-GT model is used to choose the optimal available solution for EV charging or discharging services that fulfill predefined constraints. A realistic scenario is considered as a testbed for our D-GT optimization model. Simulation results indicate that the proposed model can manage and control the interaction between EVs and D-EVSEs efficiently.

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 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 score0.450
Threshold uncertainty score0.804

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 head0.017
GPT teacher head0.241
Teacher spread0.224 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations33
Published2020
Admission routes2
Has abstractyes

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