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Record W2123597940 · doi:10.1109/tsg.2011.2136362

Hierarchical Control System for Robust Microgrid Operation and Seamless Mode Transfer in Active Distribution Systems

2011· article· en· W2123597940 on OpenAlexaff
Yasser Abdel‐Rady I. Mohamed, Amr Radwan

Bibliographic record

VenueIEEE Transactions on Smart Grid · 2011
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMicrogridVoltage droopControl theory (sociology)Controller (irrigation)ConvertersRobust controlEngineeringAC powerVoltage controllerVoltageMaximum power transfer theoremControl systemControl engineeringComputer sciencePower (physics)Voltage sourceControl (management)Electrical engineering

Abstract

fetched live from OpenAlex

This paper presents a robust hierarchical control system of distributed generation converters for robust microgrid operation and seamless transfer between grid-connected and isolated modes. The proposed control scheme employs 1) an internal model voltage controller with a variable structure control element to provide means for mitigating fast and dynamic voltage disturbances, such as dynamic voltage disturbance during mode transition and normal operation, and 2) a droop-based power-sharing controller with an active damping feature to mitigate large power-angle swings and oscillations associated with large-signal disturbances (e.g., mode transition and heavy loading conditions). The proposed voltage and power sharing controllers provide high disturbance rejection performance against voltage disturbances and power angle swings, respectively. Accordingly, robust microgrid operation with seamless transfer in the transition mode has been obtained. Comparative experimental results are presented to validate the effectiveness of the proposed control scheme.

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)0.001
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 score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.189
Teacher spread0.176 · 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

Citations305
Published2011
Admission routes1
Has abstractyes

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