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Record W2115600672 · doi:10.1109/appeec.2009.4918129

An Active Anti-Islanding Algorithm for Inverter Based Multi-Source DER Systems

2009· article· en· W2115600672 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 institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsIslandingInverterMATLABComputer scienceReliability (semiconductor)Distributed generationPower factorGridVoltageAC powerPower qualityElectronic engineeringControl theory (sociology)Voltage source inverterVoltage sourcePower (physics)EngineeringElectrical engineeringRenewable energyMathematics

Abstract

fetched live from OpenAlex

Islanding detection is an essential function for safety and reliability in grid connected distributed generation (DG) systems. Several methods for islanding detection are proposed, but most of them are not efficient for multi-source configurations, or they may produce important power quality degradation getting worst with DG penetration increasing. This paper presents an active islanding detection algorithm for voltage source inverter (VSI) based multi-source DG systems. The proposed method is based on voltage positive feedback theory. Simulations by MATLAB/Simulink/SimPowerSystems were used to evaluate its performance and its advantages concerning time response and power quality effects under critical conditions as load's unity power factor and high quality factor.

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 score0.980
Threshold uncertainty score0.807

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 head0.014
GPT teacher head0.244
Teacher spread0.230 · 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
Published2009
Admission routes1
Has abstractyes

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