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Record W4233907032 · doi:10.32920/ryerson.14653293

Multi-Modular Converters with Automatic Interleaving for Synchronous Generator Based Wind Energy System

2021· preprint· en· W4233907032 on OpenAlexaff
Maira Zulqarnain

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicWind Turbine Control Systems
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsInterleavingModular designConvertersComputer scienceRedundancy (engineering)Wind powerController (irrigation)Permanent magnet synchronous generatorElectronic engineeringControl theory (sociology)Control engineeringEngineeringVoltageElectrical engineeringControl (management)

Abstract

fetched live from OpenAlex

Among different options available for wind energy system, this research is focused on direct driven Synchronous generator based variable speed wind turbines that are connected to power grid via modular converter units. Compared to single full size power converter, modular design has higher reliability/redundancy, better harmonic performance, lower developmental cost and higher efficiency. Better harmonic performance of modular structure is possible through interleaving which effectively reduces ripple in the output current, enabling use of smaller sized filter components. Focus of this research is to design a controller that can perform automatic interleaving of modular three-phase converters used in above cited wind energy system. Developed control algorithm will have critical decisions carried out by local controllers. With minimum communication overhead the controller will ensure interleaved operation of parallel modules under all conditions. Developed control algorithm is verified through simulation and laboratory testing. Results prove effectiveness of the designed controller.

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 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 categoriesMeta-epidemiology (narrow)
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 score0.850
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.008
GPT teacher head0.186
Teacher spread0.179 · 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 teacher head, not a consensus.

Study designSimulation or modeling
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

Citations1
Published2021
Admission routes1
Has abstractyes

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