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Record W3120160437 · doi:10.1109/jestpe.2021.3050122

Fault-Tolerant Operation of the DC/DC Modular Multilevel Converter Under Submodule Failure

2021· article· en· W3120160437 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Journal of Emerging and Selected Topics in Power Electronics · 2021
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanada First Research Excellence Fund
KeywordsModular designFlexibility (engineering)Fault toleranceFault (geology)ConvertersMATLABComputer sciencePower (physics)Electronic engineeringForward converterEngineeringReliability engineeringElectrical engineeringBoost converterVoltageMathematics

Abstract

fetched live from OpenAlex

This article proposes a tailored fault-tolerant operation strategy for the dc/dc modular multilevel converter (MMC) in the case of submodules (SMs) faults. The proposed strategy utilizes the unique characteristics of the dc/dc MMC to make the post-fault operation possible without the need of adding redundant SMs. These characteristics separate the fault-tolerant operation of the dc/dc MMC from the renowned dc/ac MMC and give the converter flexibility to function at different operating points. This feature allows the converter to reduce the number of SMs needed in each arm at the cost of degraded performance or reduced power transmission. The proposed strategy is investigated through three different case studies that are simulated in the MATLAB\Simulink environment. The obtained results confirmed the effectiveness of the proposed fault-tolerant operation strategy in keeping the converter operational despite several SMs faults.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.338
Threshold uncertainty score0.425

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 head0.007
GPT teacher head0.217
Teacher spread0.211 · 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