PROTECTION SYSTEM ANALYSIS IN LV GRID, WITH HIGH DG PENETRATION, IN PARALLEL AND ISLANDING OPERATION
Bibliographic record
Abstract
The ambitious 20-20-20 targets of the European Union (EU) have been fostering the development of several projects aiming to help to comply with these goals. SENSIBLE – Storage-enabled sustainable energy for buildings and communities is a Horizon 2020 funded innovation action aiming at integrating small-scale electro-chemical, electro-mechanical and thermal storage technologies, together with Distributed Renewable Energy Sources (DRES), into distribution grid, homes and buildings. One of the main objectives of the Portuguese SENSIBLE demonstrator is to test the islanding operation of a LV with grid embedded storage devices. This paper presents the short-circuit studies that were performed for the distributed resource (DR) island system. For that purpose the actual secondary substation LV grid was modeled with MATLAB Simulink software, with real grid data provided by the DSO and with the grid embedded storage models provided by the manufacturers. The studies were performed for all foreseeable configurations (parallel and island) to ensure clearing of faulted conditions, and with different load scenarios.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".