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Record W1967199776 · doi:10.1109/pesmg.2013.6672772

A DC distribution system for power system integration of Plug-In Hybrid Electric Vehicles

2013· article· en· W1967199776 on OpenAlexaff
Mansour Tabari, Amirnaser Yazdani

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsToronto Metropolitan UniversityWestern University
Fundersnot available
KeywordsBattery (electricity)GridElectrical engineeringPhotovoltaic systemComputer sciencePower (physics)VoltageElectric power systemBattery chargerPlug-inPlug and playEngineeringAutomotive engineeringPhysics

Abstract

fetched live from OpenAlex

A DC distribution system is proposed for integration of Plug-in Hybrid Electric Vehicles (PHEVs) in public parking areas. The proposed system assumes that each PHEV is interfaced with a network of DC lines, through a corresponding bidirectional DC-DC converter (battery charger). It also assumes that a central Voltage-Sourced Converter (VSC) provides the interface between the DC network and the host AC utility grid. The proposed system is expected to be more efficient and economical than an equivalent aggregate of AC-DC battery charges connected to the AC grid, since it relieves the battery chargers from the need for a bidirectional, front-end, power-factor correction (PFC) stage. Further, due to its DC nature, the proposed system is amenable to integration of Photovoltaic (PV) modules. The paper presents a mathematical model for the proposed DC system and discusses the potential stability issues.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.233
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 source (direct Gemma or distilled Codex), 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

Citations24
Published2013
Admission routes1
Has abstractyes

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