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Record W3100647435 · doi:10.1049/iet-rpg.2019.1456

Wind turbine multiphase operational trajectory in an all‐DC wind generation system

2020· article· en· W3100647435 on OpenAlexaff
Omid Beik, Ahmad S. Al‐Adsani

Bibliographic record

VenueIET Renewable Power Generation · 2020
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsMcMaster University
Fundersnot available
KeywordsTurbineTrajectoryWind powerElectricity generationMarine engineeringComputer scienceAutomotive engineeringEnvironmental scienceControl theory (sociology)Aerospace engineeringEngineeringElectrical engineeringPhysicsControl (management)Power (physics)

Abstract

fetched live from OpenAlex

An operational trajectory and a control scheme for wind turbine generators (WTGs) in an all‐DC wind system is proposed in this study. The wind turbine includes a multiphase hybrid generator (HG) and a passive rectification stage. The WTG output is sent to an off‐shore substation using a medium‐voltage DC (MVDC) collector grid. The off‐shore substation is connected to the terrestrial grid using a high‐voltage DC (HVDC) transmission grid. The multiphase HG employs a two‐rotor topology and facilitates an active control over the wind turbine power and voltage. The proposed control scheme allows for a variable MVDC grid voltage while maintaining a wind turbine desired power under maximum power point tracking. The wind turbine trajectory is a path that wind turbine operates on as the wind velocity varies, and it is defined by HG control current, MVDC grid voltage and wind turbine power. To present the effectiveness of the proposed control and verifying the analytical model of wind turbine trajectory, a simulation platform is developed and results are presented.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.010

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 head0.033
GPT teacher head0.240
Teacher spread0.207 · 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 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

Citations20
Published2020
Admission routes1
Has abstractyes

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