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Record W2498048590 · doi:10.1109/tia.2008.916726

Understanding Power-System Stability

2008· article· en· W2498048590 on OpenAlexaboutno aff
Michael Basler, R.C. Schaefer

Bibliographic record

VenueIEEE Transactions on Industry Applications · 2008
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsnot available
Fundersnot available
KeywordsTransient (computer programming)Electric power systemSynchronizingFault (geology)Control theory (sociology)Electric power transmissionEngineeringTransmission systemPower (physics)ClearingComputer scienceTransmission (telecommunications)Electrical engineeringControl (management)Physics

Abstract

fetched live from OpenAlex

This paper discusses power-system instability and the importance of fast fault-clearing performance to aid in reliable production of power. An explanation regarding small-signal stability, high-impedance transmission lines, line loading, and high-gain fast-acting excitation systems is provided. Transient stability is discussed, including synchronizing and damping torques. The power-angle curve is used to illustrate how fault-clearing time and high initial response excitation systems can affect transient stability. The term ldquopower-system stabilityrdquo has become increasingly popular in generation and transmission. The sudden requirement for power-system stabilizers (PSSs) has created confusion about their applicability, purpose, and benefit to the system. This paper discusses the fundamentals of the PSS and its effectiveness. In today's paper industry, PSSs are being applied on larger machines in the northwest United States and Canada.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.005
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.095
GPT teacher head0.236
Teacher spread0.141 · 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

Citations97
Published2008
Admission routes1
Has abstractyes

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