MétaCan
Menu
Back to cohort
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 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: Methods · Consensus signal: Methods
Teacher disagreement score0.001
Threshold uncertainty score0.005

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 communication0.0000.000
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 head0.008
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 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
GenreMethods

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

Explore more

Same topicWind Turbine Control SystemsFrench-language works237,207