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Record W6949605856 · doi:10.5281/zenodo.2643203

PROTECTION SYSTEM ANALYSIS IN LV GRID, WITH HIGH DG PENETRATION, IN PARALLEL AND ISLANDING OPERATION

2019· article· en· W6949605856 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

VenueZenodo (CERN European Organization for Nuclear Research) · 2019
Typearticle
Languageen
FieldEngineering
TopicIslanding Detection in Power Systems
Canadian institutionsOptech (Canada)
Fundersnot available
KeywordsIslandingRenewable energyGridDistributed generationClearingMATLABResource (disambiguation)Time horizon

Abstract

fetched live from OpenAlex

The ambitious 20-20-20 targets of the European Union<br> (EU) have been fostering the development of several<br> projects aiming to help to comply with these goals.<br> SENSIBLE – Storage-enabled sustainable energy for<br> buildings and communities is a Horizon 2020 funded<br> innovation action aiming at integrating small-scale<br> electro-chemical, electro-mechanical and thermal storage<br> technologies, together with Distributed Renewable Energy<br> Sources (DRES), into distribution grid, homes and<br> buildings.<br> One of the main objectives of the Portuguese SENSIBLE<br> demonstrator is to test the islanding operation of a LV with<br> grid embedded storage devices.<br> This paper presents the short-circuit studies that were<br> performed for the distributed resource (DR) island system.<br> For that purpose the actual secondary substation LV grid<br> was modeled with MATLAB Simulink software, with real<br> grid data provided by the DSO and with the grid embedded<br> storage models provided by the manufacturers. The studies<br> were performed for all foreseeable configurations<br> (parallel and island) to ensure clearing of faulted<br> conditions, and with different load scenarios.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.155
Threshold uncertainty score0.746

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.183
Teacher spread0.173 · 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