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Record W2794424142 · doi:10.1109/tia.2018.2797068

Testing the Performance of the Digital Modular Protection for Grid-Connected Battery Storage Systems

2018· article· en· W2794424142 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

VenueIEEE Transactions on Industry Applications · 2018
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsModular designBattery (electricity)Electrical engineeringEngineeringComputer scienceGridFault (geology)RelayDigital controlCircuit breakerPower (physics)Electronic engineeringEmbedded system

Abstract

fetched live from OpenAlex

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.711
Threshold uncertainty score0.467

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.027
GPT teacher head0.217
Teacher spread0.190 · 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