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Record W2907814030 · doi:10.1109/tii.2018.2890002

On Cyber-Physical Coupling and Distributed Control in Smart Grids

2018· article· en· W2907814030 on OpenAlexafffund
Abdallah Farraj, Deepa Kundur

Bibliographic record

VenueIEEE Transactions on Industrial Informatics · 2018
Typearticle
Languageen
FieldEngineering
TopicSmart Grid Security and Resilience
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCyber-physical systemSmart gridDistributed computingComputer scienceTransmission (telecommunications)Distributed generationGridCoupling (piping)Representation (politics)Power controlControl (management)Electric power systemPower (physics)EngineeringElectrical engineeringTelecommunicationsRenewable energy

Abstract

fetched live from OpenAlex

This article focuses on characterizing the impact of communication on distributed control performance in smart grid systems. Using a cyber-physical model of the smart grid and utilizing electromechanical wave propagation in transmission systems, a holistic approach is proposed to unify cyber-physical coupling representation. This is facilitated by establishing an event-propagation paradigm relating measurements, distributed control and the physical power systems network characteristics. We investigate how power system characteristics impose limitations on distributed control performance using the proposed approach. The proposed approach is then used to derive fundamental communication delay limits for effective distributed control, and comparative analysis of distributed control performance is investigated for example distributed control scenarios.

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: Empirical
Teacher disagreement score0.163
Threshold uncertainty score0.608

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 integrity0.0000.001
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 head0.016
GPT teacher head0.227
Teacher spread0.211 · 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

Citations23
Published2018
Admission routes2
Has abstractyes

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