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An Observer-based Event-Triggered Cooperative Secondary Control of Microgrids under Switching Topologies

2023· article· en· W4388207855 on OpenAlexaff
Masood Mottaghizadeh, Innocent Kamwa, Abbas Rabiee, Seyed Masoud Mohseni‐Bonab

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsHydro-QuébecUniversité Laval
Fundersnot available
KeywordsNetwork topologyComputer scienceControl theory (sociology)Observer (physics)Control (management)Topology (electrical circuits)Computer networkEngineeringPhysicsElectrical engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

This paper presents an innovative secondary control scheme that takes into account the switching topology of the communication network. Based on the absolute values of distributed energy output variables, we propose an observer-based event-triggered cooperative secondary control scheme to regulate voltage and frequency simultaneously in stand-alone microgrids (MGs). In the propose scheme, we provide sufficient conditions to ensure the boundedness of formation errors, and also, the Zeno behavior is excluded by calculating a lower bound for the sampling intervals. Simulation results are provided to validate the proficiency and efficiency of the proposed control scheme subject to switching topologies. Furthermore, we undertake a comparative analysis between our proposed method and a contemporaneously developed control approach.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.232
Teacher spread0.222 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2023
Admission routes1
Has abstractyes

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