MétaCan
Menu
Back to cohort
Record W2130362874 · doi:10.1109/poweri.2006.1632626

Mitigation of subsynchronous resonance by SVC using PMU-acquired remote generator speed

2006· article· en· W2130362874 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.

Bibliographic record

Venue2006 IEEE Power India Conference · 2006
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsWestern University
Fundersnot available
KeywordsGenerator (circuit theory)Computer scienceResonance (particle physics)Control theory (sociology)Power (physics)Control (management)PhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

Subsynchronous resonance (SSR) is a potential problem in power systems having series compensated transmission lines. Flexible AC transmission systems (FACTS) controllers are widely applied to mitigate subsynchronous oscillations (SSO). With the advent of wide area measurement (WAM) technology, it is possible to measure the states of a large interconnected power system with synchronized phasor measurement units (PMU). In this paper the concept of using remote signals acquired through PMU has been proposed to damp SSR. An auxiliary subsynchronous damping controller (SSDC) for a static VAr compensator (SVC) using the remote generator speed as the stabilizing signal has been designed to damp subsynchronous oscillations. The IEEE first benchmark model is used to show the effectiveness of the controller. Extensive simulation results in EMTDC/PSCAD show that an SVC already installed in a transmission system with the primary objective of improving power transfer capability can also damp SSR with the auxiliary controller using remote generator speed. Finally, the effect of signal transmission delay is discussed

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.515
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.011
GPT teacher head0.213
Teacher spread0.202 · 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