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Record W2626123726 · doi:10.1109/icps.2017.7945129

Digital modular protection for grid-connected PMG-based WECSs with battery storage systems

2017· article· en· W2626123726 on OpenAlexaff
S. A. Saleh, Ryan Meng, R. McSheffery

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Systems Fault Detection
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsModular designBattery (electricity)Computer scienceElectrical engineeringFault (geology)Energy storageComputer data storageGridGenerator (circuit theory)Automotive engineeringPower (physics)EngineeringComputer hardware

Abstract

fetched live from OpenAlex

This paper develops and tests a modular digital protection for interconnected permanent magnet generator (PMG)-based wind energy conversion systems (WECSs) with battery storage. The developed protection is constructed from digital relays (modules), each of which provides protection for a specific location of the PMG-based WECS and battery storage. Moreover, each module is featured with phaselet-based fault detection. The outputs of the developed protection are trip signals to operate circuit breakers in the PMG-based WECS, battery storage, and point-of-common-coupling. The modular digital protection is implemented for experimental testing on a 5 kW PMG-based WECS that has a 2.3 kW battery storage. Test results show that the developed protection can offer fast, accurate, and reliable responses to faults occurring in different parts of the tested WECS and battery storage. In addition, test results show that the modular digital protection has minor sensitivity to the location of faults, charge/discharge cycles of the battery storage, and/or levels of power delivery to 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 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 score0.793
Threshold uncertainty score0.734

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.013
GPT teacher head0.199
Teacher spread0.186 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2017
Admission routes1
Has abstractyes

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