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Record W2106692551 · doi:10.1109/tpwrs.2004.831684

Frequency-Response Analysis of Torsional Dynamics

2004· article· en· W2106692551 on OpenAlexaff
Ahmadreza Tabesh, Reza Iravani

Bibliographic record

VenueIEEE Transactions on Power Systems · 2004
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsControl theory (sociology)Benchmark (surveying)Transfer functionFrequency domainTorqueNyquist stability criterionEigenvalues and eigenvectorsComputer scienceTime domainElectric power systemEngineeringMathematicsPhysicsPower (physics)

Abstract

fetched live from OpenAlex

This paper introduces a frequency-domain approach for investigation of the phenomenon of torsional dynamics. The Nyquist criterion is adopted by the proposed method to identify stability regions with respect to torsional oscillations. This paper also introduces two performance indices to evaluate torsional dampings and propensity of the system to experience torsional oscillations. The proposed method is an alternative approach to the eigenvalue analysis method and the complex torque method for investigation of torsional dynamics. The salient features of the method as compared with the aforementioned two methods are: 1) its computational efficiency since it utilizes the open-loop transfer-function matrix of the system and inherently more advantages for large size systems; 2) its performance indices that readily reveal "damping of" and "propensity to" a torsional oscillatory mode; and 3) its capability to formulate a multimachine system which includes both induction and synchronous machines. The proposed method is applied to the First IEEE Benchmark Systems for SSR studies and the results are verified based on comparison with those obtained from eigenvalue studies and digital-computer time-domain simulation.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.899
Threshold uncertainty score0.716

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.209
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

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

Citations36
Published2004
Admission routes1
Has abstractyes

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