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Record W4232028087 · doi:10.1109/apap.2011.6180660

Using a Real Time Digital Simulator with Phasor Measurement Unit technology

2011· article· en· W4232028087 on OpenAlexaff
Dean Ouellette, M.D. Desjardine, R. Kuffel, Yi Zhang, Eric Xu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsRTDS Technologies (Canada)
Fundersnot available
KeywordsPhasor measurement unitPhasorUnits of measurementReal-time computingSituation awarenessComputer scienceVisualizationElectric power systemALARMStability (learning theory)EngineeringPower (physics)Electrical engineeringData mining

Abstract

fetched live from OpenAlex

Testing of Phasor Measurement Units (PMU devices) is necessary for any PMU application, be it a simple visualization and archiving system or a more complex set of real-time system operations tools. PMUs are available from virtually every manufacturer of protection and monitoring equipment. PMUs can be an embedded function within relays or disturbance recorders, alternatively, PMUs can be standalone products. Many PMUs installations throughout the world are typically used for offline analysis and monitoring. PMU data can include monitoring of oscillations, angle difference, system frequency and voltage stability. Other ideas for PMU data include situational awareness, alarm and operational limit settings, state estimation and congestion management to name a few.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.712
Threshold uncertainty score0.390

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 head0.060
GPT teacher head0.219
Teacher spread0.159 · 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.

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

Citations4
Published2011
Admission routes1
Has abstractyes

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