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Record W2980773708 · doi:10.1109/tsg.2019.2948131

Autonomous Coordinated Control Scheme for Cooperative Asymmetric Low-Voltage Ride-Through and Grid Support in Active Distribution Networks With Multiple DG Units

2019· article· en· W2980773708 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueIEEE Transactions on Smart Grid · 2019
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsScheme (mathematics)GridControl theory (sociology)VoltageDistributed generationEngineeringAC powerVoltage regulationControl (management)Control engineeringComputer scienceElectrical engineeringMathematics

Abstract

fetched live from OpenAlex

This paper proposes a comprehensive autonomous coordination control scheme to achieve cooperative asymmetric low-voltage ride-through and grid support by multiple distributed generation units in an active distribution network. In addition to the decentralized nature of the proposed coordination scheme, it provides three important features: 1) a maximized flexible asymmetrical voltage support that does not affect the active current injection of individual units at the time of the support, 2) maximum support point tracking of each unit considering current, voltage, and power constraints, and 3) guided dynamic movement of the support points for each unit. The proposed scheme is examined in a practical test system, adapted from Hydro One medium-voltage distribution system in Ontario, Canada. Test results demonstrate the promising performance 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.

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 categoriesMeta-epidemiology (narrow)
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 score0.912
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.005
GPT teacher head0.185
Teacher spread0.180 · 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