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Record W2009917314 · doi:10.1109/tpwrd.2013.2258686

Design of a Backup IED for IEC 61850-Based Substation

2013· article· en· W2009917314 on OpenAlexaff
Il-Hyung Lim, T.S. Sidhu

Bibliographic record

VenueIEEE Transactions on Power Delivery · 2013
Typearticle
Languageen
FieldComputer Science
TopicNetwork Time Synchronization Technologies
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsIEC 61850BackupEthernetEngineeringEmbedded systemReliability (semiconductor)Reliability engineeringAutomationComputer scienceOperating system

Abstract

fetched live from OpenAlex

The IEC 61850-based substation automation system (SAS) provides opportunities for a new level of substation operation, enhancing operating efficiency and protection reliability with a new environment based on an Ethernet-based communication network and high-performance intelligent electronic devices (IEDs). With these changes, importance and dependence on IEDs are increasing rapidly in IEC 61850-based substations. While consideration of protection device faults has so far been infrequent, IED faults will become increasingly important in the future. Thus, this paper proposes a design of a backup IED for protection IED faults in IEC 61850-based substations. The proposed backup IED can be remotely converted into any type of protection IED without IED exchange, firmware update, or field control. The backup IED was designed through SCL engineering and file transfer functions in IEC 61850 and implemented by Windows programming with a commercially available IEC 61850 library.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.018
GPT teacher head0.217
Teacher spread0.199 · 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 source (direct Gemma or distilled Codex), 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

Citations29
Published2013
Admission routes1
Has abstractyes

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