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SINR-Dependent Event-Triggered based Distributed Secondary Frequency Regulation and Power Sharing with Jamming Attacks

2024· article· en· W4408281623 on OpenAlexaff
Pengcheng Chen, Shichao Liu, Xiaozhe Wang, Innocent Kamwa

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCognitive Radio Networks and Spectrum Sensing
Canadian institutionsUniversité LavalMcGill UniversityCarleton University
Fundersnot available
KeywordsJammingComputer scienceEvent (particle physics)Power (physics)Computer networkDistributed computingComputer securityPhysics

Abstract

fetched live from OpenAlex

This work develops a distributed proportional-integral (PI) controller combined with the signal-to-interference-plus-noise ratio (SINR)-dependent dynamic event-triggered (DET) communication strategy to cope with the frequency regulation and power sharing problems subject to jamming attacks in an inverter-based islanded microgrid. In order to simplify the controller structure, power sharing and frequency restoration can be implemented simultaneously in the designed secondary control layer instead of the traditional hierarchical control implementation. Besides, the dynamic event-triggered communication strategy configured with each secondary controller can adaptively adjust the triggered threshold based on the SINR signal, which can reduce the congestion of communication networks caused by jamming attacks and ensure system control performance. A cyber-physical microgrid testbed is built based on the real-time simulator, OPAL-RT, and network simulation software, EXata, to verify the effectiveness of the proposed SINR-dependent event-triggered based distributed secondary controller.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.965
Threshold uncertainty score0.692

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 communication0.0010.001
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 head0.009
GPT teacher head0.228
Teacher spread0.219 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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