MétaCan
Menu
Back to cohort
Record W4226027897 · doi:10.1109/access.2022.3171346

A DC-Side Fault-Tolerant Bidirectional AC-DC Converter for Applications in Distribution Systems

2022· article· en· W4226027897 on OpenAlexafffund
Sandeep Kaler, Amirnaser Yazdani

Bibliographic record

VenueIEEE Access · 2022
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of CanadaRyerson University
KeywordsMATLABComputer scienceFault (geology)ConvertersForward converterSoftwareFrame (networking)VoltageTopology (electrical circuits)Power (physics)Flyback converterElectronic engineeringCharge pumpControl theory (sociology)Electrical engineeringBoost converterCapacitorControl (management)EngineeringPhysics

Abstract

fetched live from OpenAlex

This paper proposes an ac-dc converter for dc distribution systems. The proposed converter has a simple structure, offers bidirectional power flow capability, and is robust to dc-side faults. Based on the developed dynamic model, the converter is current-controlled in a rotating reference frame, meaning it is also protected against ac-side faults. Insight on the design of the specific control parameters for proper operation of the various control loops is also provided. Furthermore, it is shown that the minimum permissible dc-link voltage of the converter is the same as that of a conventional voltage-sourced converter. Time-domain simulation studies in the MATLAB and Simulink software environments, as well as a 1.25-$kW$experimental prototype confirm the effectiveness of the proposed converter under various normal and faulted operating scenarios.

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 score0.003
Threshold uncertainty score0.010

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.021
GPT teacher head0.270
Teacher spread0.249 · 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

Citations3
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueIEEE AccessSame topicHVDC Systems and Fault ProtectionFrench-language works237,207