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Record W2124282653 · doi:10.1109/pes.2011.6039262

Voltage regulation in distribution feeders with high DG penetration: From traditional to smart

2011· article· en· W2124282653 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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOptimal Power Flow Distribution
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSmart gridVoltage regulationVoltageVoltage regulatorPenetration (warfare)Distribution gridDistributed power generationGridDistributed generationComputer scienceRegulatorLow voltageControl (management)EngineeringControl theory (sociology)Electrical engineeringOperations researchRenewable energyMathematicsBiology

Abstract

fetched live from OpenAlex

This paper addresses the negative impacts of distributed generations (DGs) on the utility voltage regulators and hence on the voltage profile of distribution feeders. These negative impacts have been verified through carrying out different simulations on an unbalanced distribution feeder. The results show that a significant regulation problem might arise due to the increased levels of DG penetration correlated with traditional utility voltage regulator's control practices. Consequently, DGs inevitably need to cooperate and communicate with distribution network voltage control devices. Smart grid generally aims to combine the existing utility grids with new digital technology to substantially improve the overall efficiency of the network. In this paper, a communication based multi-agent cooperative control structure has been proposed as a solution to mitigate the voltage regulation issues in distribution feeders with high DG penetration.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.779
Threshold uncertainty score0.862

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 integrity0.0000.000
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 head0.019
GPT teacher head0.172
Teacher spread0.153 · 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

Quick stats

Citations53
Published2011
Admission routes1
Has abstractyes

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