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Passive Fault-Tolerant Control of PWM Converter in a Hybrid AC/DC Microgrid

2019· article· en· W3011842694 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsConcordia University
Fundersnot available
KeywordsMicrogridPhotovoltaic systemPulse-width modulationFault (geology)Renewable energyComputer scienceFault toleranceMATLABDistributed generationEngineeringElectronic engineeringControl theory (sociology)Electrical engineeringControl (management)Reliability engineeringVoltage

Abstract

fetched live from OpenAlex

This paper aims to present a novel fault-tolerant control approach for an AC/DC pulse-width modulation (PWM) converter operating in a microgrid framework. A group of interconnected loads and renewable distributed energy resources such as wind farm, solar photovoltaic farm, and a battery energy storage are considered to form a microgrid. The control system related to the AC/DC converter aims at tolerating the fault effects due to power-loss malfunction in the solar photovoltaic system. To address this issue, a passive fault-tolerant control method based on fuzzy logic is proposed and the effectiveness of the designed scheme is demonstrated in an advanced microgrid benchmark model implemented in MATLAB/Simulink environment.

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: Empirical
Teacher disagreement score0.486
Threshold uncertainty score0.621

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.002
GPT teacher head0.158
Teacher spread0.156 · 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

Quick stats

Citations13
Published2019
Admission routes1
Has abstractyes

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