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Record W1984926968 · doi:10.1109/ecce.2012.6342350

Coordinated active/reactive power control for flicker mitigation in distributed wind power

2012· article· en· W1984926968 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWind Turbine Control Systems
Canadian institutionsMcGill University
Fundersnot available
KeywordsAC powerFlickerWind powerPower factorControl theory (sociology)Power controlPower (physics)Line (geometry)Compensation (psychology)Volt-ampere reactiveEngineeringComputer scienceVoltageVoltage optimisationElectrical engineeringAutomotive engineeringControl (management)PhysicsMathematics

Abstract

fetched live from OpenAlex

Flicker mitigation in variable-speed wind generators can be approached by reactive power control utilizing the power-electronic converter of the machine, a technique that is bound by several factors including the network X/R ratio, line current limits and the instantaneous output of the machine. The highest flicker level is observed as the machine approaches its rated output, under such conditions in sites with favorable wind resource, sole reactive power compensation would necessitate overrated operation for long periods and increased line currents or otherwise the reactive power margin narrows possibly resulting in impaired capability in reducing flicker to compatible levels. This paper proposes coordinated power curtailment and reactive power control and assesses the feasibility of its implementation in reducing variable-speed wind generators flicker emission under high wind speed conditions. The amount of active power to be curtailed is quantified based on the observed decrease in short-term flicker Pst with respect to power factor settings.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.596
Threshold uncertainty score0.821

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 head0.005
GPT teacher head0.208
Teacher spread0.203 · 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

Quick stats

Citations7
Published2012
Admission routes1
Has abstractyes

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