MétaCan
Menu
Back to cohort
Record W1979888601 · doi:10.1109/pes.2010.5590051

A review of active distribution networks enabling technologies

2010· review· en· W1979888601 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
Typereview
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsHydro-QuébecMcGill University
Fundersnot available
KeywordsComputer scienceActive networkingDistribution (mathematics)Distributed computingComputer networkMathematics

Abstract

fetched live from OpenAlex

High levels of distributed generation have been installed in power systems and even a greater amount is expected to be deployed in the near future, with a large percentage likely to come from renewable energy sources. As such, Distribution System Operators (DNOs) will need to change their old “business as usual” passive approach, to one that adopts integration of control and communication technologies, together with emerging distribution network technologies, as a means of accommodating new generation in an optimal and economical manner. This paper presents a review of some of the impacts associated with the integration of distributed generation, together with some active distribution networks enabling technologies, intended to deal with the aforementioned problems. In particular, the present review focuses on technologies that are in advanced stages of Research and Development, or are even at the trial stage or are commercially available. However, further analyses are required in order to develop cheaper and more secure means to the increasing Distributed Generation connections.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.937
Threshold uncertainty score0.667

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.011
GPT teacher head0.245
Teacher spread0.234 · 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

Citations101
Published2010
Admission routes1
Has abstractyes

Explore more

Same topicMicrogrid Control and OptimizationFrench-language works237,207