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Record W3044656340 · doi:10.3390/app10144988

Smart Power Electronics–Based Solutions to Interface Solar-Photovoltaics (PV), Smart Grid, and Electrified Transportation: State-of-the-Art and Future Prospects

2020· article· en· W3044656340 on OpenAlexafffund
Sandra Aragon-Aviles, Ashutosh Trivedi, Sheldon S. Williamson

Bibliographic record

VenueApplied Sciences · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsOntario Tech University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElectrificationPhotovoltaic systemPhotovoltaicsElectrical engineeringPower electronicsEngineeringConvertersSmart gridGreenhouse gasAutomotive engineeringElectricityVoltage

Abstract

fetched live from OpenAlex

The need to reduce the use of fossil fuels and greenhouse gas (GHG) emissions produced by the transport sector has generated a clear increasing trend in transportation electrification and the future of energy and mobility. This paper reviews the current research trends and future work for power electronics-based solutions that support the integration of photovoltaic (PV) energy sources and smart grid with charging systems for electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEV). A compressive overview of isolated and non-isolated DC–DC converters and AC–DC converter topologies used to interface the PV-grid charging facilities is presented. Furthermore, this paper reviews the modes of operation of the system currently used. Finally, this paper explores the future roadmap of research for power electronics solutions related to photovoltaic (PV) systems, smart grid, and transportation electrification.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.502

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.012
GPT teacher head0.234
Teacher spread0.222 · 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 designBench or experimental
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

Citations29
Published2020
Admission routes2
Has abstractyes

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