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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 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

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.

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: Empirical
Teacher disagreement score0.364
Threshold uncertainty score1.000

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 communication0.0000.001
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 head0.033
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