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Record W2122053311 · doi:10.1109/pesw.2002.985195

Small signal analysis of hydro-turbine governors in large interconnected power plants

2003· article· en· W2122053311 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venue2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309) · 2003
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsHydro-Québec
Fundersnot available
KeywordsTurbineSIGNAL (programming language)Power (physics)Hydraulic turbinesComputer scienceEnvironmental scienceEngineeringAerospace engineeringPhysics

Abstract

fetched live from OpenAlex

The paper describes a transient stability program (TSP) based approach to identify numerically, a state-space, small-signal model of the open-loop system seen by the hydro-turbine governor during its normal operation. This single-input multiple-output model is validated successfully by comparing actual closed-loop responses computed in the TSP with those simulated in Matlab using the linearized model. For illustration, three governing systems found in the Hydro-Quebec's grid are studied: (1) a mechanical hydraulic; (2) a Woodward PID; and (3) a classical Neyrpic's governor. System performance with respect to the speed of response, interarea modes sensitivity and closed-loop gain and phase margins is assessed, evidencing the somewhat detrimental impact of the derivative control term for interconnected operation. Overall, the small-signal analysis approach devised appears well-suited for determining and/or assessing unit-connected settings of hydro-turbine speed governing systems.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.757
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.194
Teacher spread0.184 · 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