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Record W2101093329 · doi:10.1109/pesw.2002.985103

Dual configuration, dual setting, digital power system stabilizer-simulation and tuning experience at Manitoba Hydro

2003· article· en· W2101093329 on OpenAlexaffabout
B.A. Archer, Lorne Midford, J.B. Davies

Bibliographic record

Venue2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309) · 2003
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsManitoba Hydro
Fundersnot available
KeywordsStabilizer (aeronautics)Electric power systemControl theory (sociology)Dual (grammatical number)TorquePower (physics)Computer scienceModulation (music)Transmission (telecommunications)EngineeringControl engineeringElectrical engineeringPhysicsMechanical engineeringControl (management)Acoustics

Abstract

fetched live from OpenAlex

This paper describes a digital power system stabilizer which can automatically switch between two different sets of settings and operate as an electric power input type and an integral-of-accelerating power input type. The requirements for such a stabilizer along with techniques to facilitate its implementation on two hydraulic units which are switchable between an isolated AC system feeding an HVDC double bipole and a parallel, relatively weak, 230 and 138 kV AC transmission system, is provided. Stabilizer tuning based on load modulation is presented. Results from eigenvalue analysis and dynamic stability studies demonstrate the effectiveness of this stabilizer in damping both inter-area and inter-plant electromechanical modes, as well as reducing the undesirable effects of low gate mechanical torque oscillations.

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)0.000
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 score0.036
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.205
Teacher spread0.195 · 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

Citations7
Published2003
Admission routes2
Has abstractyes

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Same venue2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309)Same topicPower System Optimization and StabilityFrench-language works237,207