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Feasibility Study of Renewable Energy Integrated Electric Vehicle Charging Infrastructure

2016· book-chapter· en· W2559532096 on OpenAlexaff
Azhar Ul-Haq, M. Athiba Azhar

Bibliographic record

VenueAdvances in information security, privacy, and ethics book series · 2016
Typebook-chapter
Languageen
FieldEngineering
TopicElectric Vehicles and Infrastructure
Canadian institutionsÉcole de Technologie SupérieureUniversity of New Brunswick
Fundersnot available
KeywordsInterfacingRenewable energyElectric vehicleSmart gridEngineeringCharging stationInformation and Communications TechnologyAutomotive engineeringElectrical engineeringTelecommunicationsComputer sciencePower (physics)

Abstract

fetched live from OpenAlex

This chapter presents a detailed study of renewable energy integrated charging infrastructure for electric vehicles (EVs) and discusses its various aspects such as siting requirements, standards of charging stations, integration of renewable energy sources for powering up charging stations and interfacing devices between charging facilities and smart grid. A smart charging station for EVs is explained along with its essential components and different charging methodologies are explained. It has been recognized that the amalgamation of electric vehicles in the transportation sector will trigger power issues due to the mobility of vehicles beyond the stretch of home area network. In this regard an information and communication technology (ICT) based architecture may support EVs management with an aim to enhance the electric vehicle charging and energy storage capabilities with the relevant considerations. An ICT based solution is capable of monitoring the state of charge (SOC) of EV batteries, health and accessible amount of energy along with the mobility of EVs.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.875
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 communication0.0000.004
Open science0.0000.000
Research integrity0.0010.001
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 head0.235
Teacher spread0.226 · 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 designTheoretical or conceptual
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

Citations0
Published2016
Admission routes1
Has abstractyes

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