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Record W2207357829 · doi:10.1109/vppc.2015.7352997

Power Quality Device for Future Household Systems with Fast Electric Vehicle Charging Station

2015· article· en· W2207357829 on OpenAlexaff
Alireza Javadi, Auguste Ndtoungou, Handy Fortin Blanchette, Kamal Al‐Haddad

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsUniversité du Québec
Fundersnot available
KeywordsPower factorVoltageElectrical engineeringTotal harmonic distortionActive filterRenewable energySmart gridPower qualityAC powerEngineeringGridElectric power systemHarmonicCompensation (psychology)HarmonicsSwitched-mode power supplyElectronic engineeringComputer sciencePower (physics)

Abstract

fetched live from OpenAlex

This paper investigates on power quality improvement of Smart residential buildings with Electric vehicle charging station. A multilevel Transformerless Hybrid Series Active Filter (THSeAF) is proposed to address power quality issues related to both current and voltage. The proposed configuration assists integration of renewable energy sources to ensure a sustainable supply. The controller is based on a two separated single-phase proportional plus resonant (PR) regulator to prevent current harmonic distortions of various non-linear loads to flow into the utility. The proposed topology is able to instantly correct the power factor as well as cleaning the grid's current, while protecting consumers from voltage disturbances, sags, and swells during a grid perturbation. Aspects of harmonic compensation and voltage restoration for a 120/240V residential system are analyzed along with the proposed solution to overcome power quality 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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.002

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 head0.043
GPT teacher head0.295
Teacher spread0.251 · 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 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

Citations8
Published2015
Admission routes1
Has abstractyes

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