MétaCan
Menu
Back to cohort
Record W2051568285 · doi:10.1109/apec.2014.6803542

A wind energy conversion system with enhanced power harvesting capability for low cut-in speeds

2014· article· en· W2051568285 on OpenAlexaff
Ali Moallem, Alireza Bakhshai, Praveen Jain

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsQueen's University
Fundersnot available
KeywordsWind powerVoltageLow voltageConvertersRenewable energyElectrical engineeringPower (physics)Boost converterComputer scienceEngineeringElectronic engineering

Abstract

fetched live from OpenAlex

This paper proposes a new technique for enhancement of energy extraction capabilities in wind energy conversion systems with low cut-in speed. The dc-link voltage is maintained by the grid-side converter in wind energy systems equipped with back-to-back three-phase inverters. This voltage is required to be higher than a certain value to ensure proper operation of the grid-side converter. On the other hand, at low generator voltages, switching times for the generator-side converter cannot be realized due to practical limitations. Accordingly, the system cannot harvest energy at low cut-in speeds. A power electronics system consisting of an isolated SEPIC converter along with an upper-hand control scheme has been introduced and employed to alleviate the aforementioned power extraction issue. The proposed solution, allows for excellent power extraction even at low cut-in speeds by maintaining an appropriate dc-link voltage at various operation conditions. Therefore increasing the overall renewable generation capability in wind-energy systems. The proposed solution can be incorporated in existing wind energy conversion systems with back-to-back three-phase inverters with slight hardware and software modifications. The integrated isolated SEPIC converter handles a fraction of the rated power, therefore leads to reduced cost and size compared to existing systems with integrated full-rated boost converters.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
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)0.0020.001

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 head0.003
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

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
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

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

Same topicMicrogrid Control and OptimizationFrench-language works237,207