Testing the Performance of the Digital Modular Protection for Grid-Connected Battery Storage Systems
Bibliographic record
Abstract
This paper presents the performance evaluation of the digital modular protection for grid-connected battery storage systems (BSSs). The tested digital protection is designed using multiple digital relays that are located at different parts of the protected BSS. Each digital relay is featured with a phaselet-based fault detection to ensure accuracy and response speed. The outputs of the digital modular protection are control signals that operate circuit breakers in the charging and discharging circuits, battery units, and the point of common coupling. The tested digital modular protection is implemented for performance evaluation using a 250-kW grid-connected BSS that is charged through a 3φ ac-dc power electronic converter (PEC) and discharged through a 3φ dc-ac PEC. Performance results show that the digital modular protection can initiate fast, accurate, and reliable responses to faults occurring in different parts of the protected BSS. These response features have a negligible sensitivity to the type and/or location of faults, the charge/discharge mode of operation, and/or levels of power exchange with the host grid.
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.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".