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Record W2040528610 · doi:10.1049/iet-gtd:20070021

Power system damping from real and reactive power modulations of voltage-source-converter station

2008· article· en· W2040528610 on OpenAlexaff
Shenhao Ruan, G.-J. Li, B.T. Ooi, Y.Z. Sun

Bibliographic record

VenueIET Generation Transmission & Distribution · 2008
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsMcGill University
Fundersnot available
KeywordsVoltage sourceElectric power systemConvertersPhotovoltaic systemAC powerControllabilityControl theory (sociology)Renewable energyWind powerEngineeringPower (physics)VoltageElectrical engineeringElectronic engineeringComputer sciencePhysicsMathematics

Abstract

fetched live from OpenAlex

As gas turbines, wind farms, run-of-river hydro, photovoltaic and other renewable energy sources are becoming a growing component in the power system, the feasibility of applying the controllability of their expensive frequency-changers [based on voltage-source converters or (VSCs)] is examined to provide system damping. It is shown that irrespective of the location of the VSC-frequency changers along the transmission line, significant damping is available by the combined control of real and reactive power modulations. The finding is reached by eigenvalue analysis of the linearised equations and confirmed by digital simulation (PSCAD/EMTDC). Digital simulation is also applied to evaluate the size of injected complex power required for the best damping for a given converter rating.

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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0030.000

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 head0.012
GPT teacher head0.202
Teacher spread0.190 · 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

Citations36
Published2008
Admission routes1
Has abstractyes

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