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Record W3026328794 · doi:10.1109/tia.2020.2996537

Simplified Hybrid AC–DC Microgrid With a Novel Interlinking Converter

2020· article· en· W3026328794 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Industry Applications · 2020
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsWestern University
Fundersnot available
KeywordsConvertersMicrogridElectronic engineeringPower (physics)VoltageComputer scienceElectrical engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

Hybrid ac-dc microgrids (HMG) have become more popular recently because of their superior features in comparison with pure ac and dc microgrids (MGs). HMGs have fewer power converters and are more flexible than pure ac and dc MGs, but the number of converters in HMG is still significant, especially when the dc part of HMG has several voltage levels. A new simplified and more flexible architecture for HMGs that features a new multiport interlinking converter (IC) is proposed in this article. Using the proposed IC, the number of power electronic converters in an HMG with several dc bus voltages can be reduced without increasing the number of active switches in the IC or the complexity of its control system. In this article, the new simplified HMG architecture is presented, and the operation of the proposed IC as a single unit and as a part of a simplified HMG are explained, along with its features. Experimental results obtained from a scaled-down prototype are also presented to confirm the feasibility of the multiport interlinking converter. Simulation results that show the effect of load variations in the intermediate bus architecture dc bus on the operation of the HMG are also presented as well.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.991
Threshold uncertainty score0.920

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.200
Teacher spread0.186 · 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