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Record W2180380942 · doi:10.1109/tpwrs.2012.2227845

A Type-4 Wind Power Plant Equivalent Model for the Analysis of Electromagnetic Transients in Power Systems

2012· article· en· W2180380942 on OpenAlexaff
Dalia Hussein, Mahmoud Matar, Reza Iravani

Bibliographic record

VenueIEEE Transactions on Power Systems · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLightning and Electromagnetic Phenomena
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsWind powerControl theory (sociology)Induction generatorEquivalent circuitTurbineElectric power systemComponent (thermodynamics)Frequency responsePower (physics)EngineeringRange (aeronautics)Control engineeringComputer scienceElectrical engineeringPhysicsControl (management)Voltage

Abstract

fetched live from OpenAlex

This paper introduces an accurate and computationally efficient reduced-order dynamic equivalent of a Type-4-based wind power plant (WPP) for the analysis of electromagnetic transients (EMTs) in the power system external to the WPP. The proposed model significantly reduces the computational resources and the simulation run time while preserving the WPP response fidelity in the desired frequency range, e.g., 0 to 50 kHz. The proposed WPP equivalent model is composed of two parts: 1) a frequency-dependent equivalent model which represents the WPP passive component in the entire frequency range and 2) a dynamic equivalent model that represents the WPP supervisory control and the aggregated low-frequency dynamics of wind-turbine generator (WTG) units. The latter can be constructed from the: 1) dynamic generic models; 2) vendor-specific models; or 3) user-defined models. The proposed model is incorporated as a software module in the PSCAD/EMTDC environment, and its efficiency and accuracy are verified based on comparing the results with those of a detailed model.

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)0.001
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.018
GPT teacher head0.244
Teacher spread0.226 · 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

Citations49
Published2012
Admission routes1
Has abstractyes

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