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Record W2599246550 · doi:10.1109/tpwrd.2017.2689792

Safe Operation of DFIG-Based Wind Parks in Series-Compensated Systems

2017· article· en· W2599246550 on OpenAlexafffund
Ulas Karaagac, Jean Mahseredjian, Simon Jensen, Richard Gagnon, Martin Fecteau, Ilhan Koçar

Bibliographic record

VenueIEEE Transactions on Power Delivery · 2017
Typearticle
Languageen
FieldEngineering
TopicWind Turbine Control Systems
Canadian institutionsHydro-QuébecPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDoubly fed electric machineElectric power systemControl theory (sociology)Transient (computer programming)Electric power transmissionTransmission lineEngineeringTransmission systemPower electronicsSeries (stratigraphy)Automatic frequency controlWind powerControl systemInduction generatorGenerator (circuit theory)Control engineeringTransmission (telecommunications)Power (physics)AC powerControl (management)VoltageComputer scienceElectrical engineering

Abstract

fetched live from OpenAlex

Subsynchronous control interaction (SSCI) is the interaction between the power-electronics control and the series-compensated transmission system that occurs at frequencies below the system nominal frequency. SSCI may occur between the doubly-fed induction generator (DFIG) control system and the series-compensated transmission line, to which the wind park (WP) is connected. Not only do the DFIG control system parameters, but also the WP operating conditions have a significant impact on SSCI. In this paper, the impact of WP operating conditions and DFIG control system parameters on SSCI is analyzed in detail. Guidelines are presented for modifying the DFIG control system parameters to ensure safe operation and acceptable transient responses due to faults. This paper also examines the accuracies of various analytical tools used for SSCI problem identification and proposes a new frequency scan analysis approach for accurate prediction of potential SSCI problems.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.206
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), 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

Citations60
Published2017
Admission routes2
Has abstractyes

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