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Record W1980207029 · doi:10.1109/tdc.2014.6863168

SSR alleviation by STATCOM in induction generator based wind farm connected to series compensated line

2014· article· en· W1980207029 on OpenAlexaff
Akshaya Moharana, Rajiv K. Varma, Ravi Seethapathy

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWind Turbine Control Systems
Canadian institutionsWestern University
Fundersnot available
KeywordsInduction generatorControl theory (sociology)TurbineWind powerTransient (computer programming)Fault (geology)Controller (irrigation)TorqueGenerator (circuit theory)EngineeringVoltageSeries (stratigraphy)Compensation (psychology)Computer scienceElectrical engineeringPower (physics)PhysicsControl (management)

Abstract

fetched live from OpenAlex

In this paper, a STATCOM with voltage controller is proposed to mitigate the potential of SSR in a series compensated IG based wind farm. Detailed eigenvalue analysis is performed to demonstrate that Induction Generator effect SSR is successfully alleviated by STATCOM. The results are validated through electromagnetic transient simulation with PSCAD/EMTDC. The impacts of symmetrical fault at different locations and collector cables are investigated and the effectiveness of the proposed STATCOM controller is illustrated. It is shown that a three phase fault close to the wind farm may cause severe oscillations in the PCC voltage, electromagnetic torque and shaft torque of the wind turbine generator. To examine this situation, an equivalent circuit analysis is presented, which predicts the threshold resonant speeds within which the wind turbine becomes unstable. The study is extended to other commercially available induction generators, which also shows the potential for SSR even at realistic levels of series compensation levels, and the capability of the proposed STATCOM controller to obviate its occurrence.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.582
Threshold uncertainty score0.690

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 head0.007
GPT teacher head0.189
Teacher spread0.182 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

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