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Record W1987516915 · doi:10.1109/tpwrd.2013.2282264

Unintentional Islanding of Distributed Generation—Operating Experiences From Naturally Occurred Events

2014· article· en· W1987516915 on OpenAlexaff
Chun Li, Jason Savulak, Robert Reinmuller

Bibliographic record

VenueIEEE Transactions on Power Delivery · 2014
Typearticle
Languageen
FieldEngineering
TopicIslanding Detection in Power Systems
Canadian institutionsHydro One (Canada)
Fundersnot available
KeywordsIslandingDistributed generationCompensation (psychology)EngineeringElectricity generationLoad SheddingWind powerAC powerElectric power systemDistributed power generationComputer sciencePower (physics)Reliability engineeringElectrical engineeringVoltageRenewable energy

Abstract

fetched live from OpenAlex

This paper presents original records of distributed-generation unintentional islanding events in three categories. The islands were formed by naturally occurred faults without the transfer trip initiated to generation facilities. Hydraulic, natural gas, and wind generators were involved in the events. The records exemplify important issues in DG anti-islanding planning, such as coordination with underfrequency (or undervoltage) load shedding, reactive power compensation, generation-to-load ratio, reclosing coordination, etc. The events reported in this paper can serve as first-hand references in applying IEEE Standard 1547 to distributed generation anti-islanding planning and operation.

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.209
Teacher spread0.197 · 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 designObservational
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

Citations35
Published2014
Admission routes1
Has abstractyes

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