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Record W1825905760 · doi:10.1109/pesw.2001.917213

Recommended modeling of power system governing response

2002· article· en· W1825905760 on OpenAlexaboutno aff
R.P. Schulz, R.J. O'Keefe

Bibliographic record

Venue2001 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.01CH37194) · 2002
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsnot available
Fundersnot available
KeywordsInterconnectionFrequency responseElectric power systemPower (physics)Response timeAutomatic Generation ControlAutomatic frequency controlControl theory (sociology)Electricity generationComputer sciencePower stationControl (management)EngineeringElectrical engineeringTelecommunicationsPhysics

Abstract

fetched live from OpenAlex

Summary form only given. Power plant governing response is the prompt automatic increase in generation in response to decreases of system frequency. This governing response, also called primary frequency regulation, acts to preserve the balance between generation and load across the interconnected power system; it provides tight frequency control within 2 to 3 seconds after trips of units. Power plant governing response, the change in generation normalized by the change in frequency, has units of MW/Hz; it is commonly expressed in the US and Canada as MW per 0.1 Hz. Both power system operating and planning personnel have become increasingly aware of the fact that power plant governing response is considerably less than expected and planned for. This difference, "the governing problem" is seen after abrupt changes in generation or served load; the sustained component of the simulated response of system frequency is much closer to 60 Hertz than the recorded response. This presentation presents recordings of unit and interconnection response to events that illustrate: the nature of the governing problem from an interconnection view; individual unit responses, which suggest classes of nonresponsiveness; and results of simulations compared to recordings of the same events.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.560
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.198
Teacher spread0.181 · 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.

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

Citations1
Published2002
Admission routes1
Has abstractyes

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