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Record W2484336718 · doi:10.1109/pedg.2016.7527029

A New Slip Mode Frequency Shift Islanding Detection Method for single phase grid connected inverters

2016· article· en· W2484336718 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIslanding Detection in Power Systems
Canadian institutionsQueen's University
Fundersnot available
KeywordsIslandingInverterGridComputer scienceFunction (biology)Mode (computer interface)Electronic engineeringControl theory (sociology)EngineeringVoltageElectrical engineeringDistributed generationMathematics

Abstract

fetched live from OpenAlex

This paper presents a new slip mode frequency shift islanding detection method (SMS IDM). This new method uses a non-sinusoidal function for drifting the inverter phase angle. The Non-Detection Zone (NDZ) of the SMS IDM with sinusoidal function has been calculated and it has been shown that if the quality factor and/or the resonance frequency of the load changes during the inverter operation time, SMS IDM with sinusoidal function fails to detect islanding for a specific range of variation. It is shown in the paper that SMS IDM with the new function has a smaller NDZ area compared to the SMS IDM with sinusoidal function. Simulation and experimental results verify the results of the proposed new method.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.972
Threshold uncertainty score0.696

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 communication0.0000.000
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 head0.017
GPT teacher head0.270
Teacher spread0.253 · 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

Quick stats

Citations11
Published2016
Admission routes1
Has abstractyes

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