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Record W2991492906 · doi:10.1139/tcsme-2019-0056

Research on rotating speed control of the vertical axis hydraulic wind turbine

2019· article· en· W2991492906 on OpenAlexvenueno aff
Chao Ai, Yabin Zhang, Cunde Jia, Liang Zhang, Xiangdong Kong

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicWind Turbine Control Systems
Canadian institutionsnot available
Fundersnot available
KeywordsVertical axis wind turbineTurbineWind speedThrottleAerodynamicsControl theory (sociology)Tip-speed ratioMarine engineeringEngineeringAutomotive engineeringComputer scienceMechanical engineeringAerospace engineeringMeteorologyPhysicsControl (management)

Abstract

fetched live from OpenAlex

In this paper, the vertical axis wind turbine was selected as the research object, with emphasis on the characteristics of the accurate grid-connected motor speed control. First, the mathematic model of the vertical axis wind turbine and hydraulic main drive system was established, the aerodynamic characteristics of the vertical axis wind turbine were analyzed, and the regularity of the periodic fluctuation of the output speed of the vertical axis wind turbine was obtained. According to the wind speed prediction curve and the aerodynamic model of the vertical axis wind turbine, the characteristic curve of the wind turbine speed was obtained. Then according to the grid connection actual demand of the wind turbine, the high-precision grid-connected control strategy of the variable motor swivel and proportional throttle valve based on wind speed prediction was proposed, and the variable motor speed was found to be stable at 1500 ± 2 r/min, realizing the rapid and accurate grid-connected requirements. Finally, the control method was simulated and validated by Matlab/Simulink software, and the control method was validated experimentally on a semi-physical simulation test bench of a 30 kVA hydraulic wind turbine, which achieved a satisfactory control effect.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.513

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.229
Teacher spread0.214 · 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.

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

Citations4
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicWind Turbine Control SystemsFrench-language works237,207