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Record W2762170091 · doi:10.1049/iet-gtd.2016.2086

Reactive power sharing improvement of droop‐controlled DFIG wind turbines in a microgrid

2017· article· en· W2762170091 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 Generation Transmission & Distribution · 2017
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsVoltage droopMicrogridWind powerDoubly fed electric machineAC powerPower (physics)Automotive engineeringControl theory (sociology)Computer scienceElectrical engineeringVoltageEngineeringControl (management)Physics

Abstract

fetched live from OpenAlex

This study presents an innovative control scheme to improve the power sharing among doubly‐fed induction generator (DFIG) wind units in a medium‐voltage (MV) microgrid. The control objectives of DFIGs in an islanded mode of microgrid operation are to achieve: (i) stabilisation of the microgrid voltage amplitude and frequency, (ii) proper active/reactive power sharing among wind units. To satisfy these requirements, the DFIG control loop based on the traditional droop control is designed. This method, however, cannot satisfactorily operate in a MV microgrid with dominantly resistive line impedances from power sharing point of view. To overcome this problem, a modified control strategy is proposed in this study. The mathematical modelling is developed, and time‐domain simulations are presented to verify the novel control scheme in a typical microgrid case study.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.440
Threshold uncertainty score0.752

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 communication0.0000.000
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 head0.009
GPT teacher head0.221
Teacher spread0.211 · 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