MétaCan
Menu
Back to cohort
Record W4233087042 · doi:10.32920/ryerson.14651763.v1

Direct voltage control for stand-alone wind energy conversion systems with energy storage

2021· preprint· en· W4233087042 on OpenAlexaff
Wei Huang

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicWind Turbine Control Systems
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsEnergy storageVoltageWind powerControl theory (sociology)Power (physics)Power controlElectric power systemGenerator (circuit theory)Electrical engineeringComputer scienceEngineeringControl (management)Physics

Abstract

fetched live from OpenAlex

A control method for the stand-alone wind power generation system with induction generator and energy storage devices is proposed in this thesis. A fixed-speed self-excited induction generator is directly connected to the standalone power system, while battery powered energy storage devices are employed to balance the system power flow. A DC-AC power converter is connected between the energy storage device and the standalone power system, which maintains the voltage and frequency constant. Direct voltage control with current limits is developed for the converter with dynamic fast response. Mathematical models are developed to analysis the system performance as well as to design the lead-lag regulators in the control system. The proposed system is verified in the simulation and experiment.

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)0.000
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: none
Teacher disagreement score0.982
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.006
GPT teacher head0.177
Teacher spread0.170 · 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.

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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicWind Turbine Control SystemsFrench-language works237,207