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Record W1596602136 · doi:10.1109/isgt.2015.7131838

A cyber-enabled stabilizing controller for resilient smart grid systems

2015· article· en· W1596602136 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsUniversity of Toronto
FundersDivision of Electrical, Communications and Cyber SystemsNational Science Foundation
KeywordsControl theory (sociology)Controller (irrigation)Electric power systemPhasor measurement unitControl engineeringComputer sciencePhasorFeedback linearizationParametric statisticsSmart gridGridAutomatic frequency controlFrequency gridPower (physics)EngineeringControl (management)MathematicsTelecommunications

Abstract

fetched live from OpenAlex

A parametric controller is proposed for the frequency and phase stabilization after the occurrence of a disturbance in the power grid. The proposed controller is based on the feedback linearization control theory. To drive the frequency of the system generators to stability, the controller relies on receiving timely phasor measurement unit (PMU) readings about the power grid to employ fast-acting flywheels that are situated near the synchronous generators in order to balance a swing equation model of the synchronous generators. The advantages of the proposed controller are that it is tunable and integrates well with existing governor controls in contrast to other forms of PMU-based control. Numerical results show the effectiveness of the proposed controller when applied to the New England power system. Further, a comparison is drawn between the controller and recently-proposed nonlinear controllers for transient stability.

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 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 score0.984
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.028
GPT teacher head0.232
Teacher spread0.204 · 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

Quick stats

Citations23
Published2015
Admission routes1
Has abstractyes

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