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Record W1895297768 · doi:10.1109/jestpe.2015.2457671

A Reference Impedance-Based Passive Islanding Detection Method for Inverter-Based Distributed Generation System

2015· article· en· W1895297768 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Journal of Emerging and Selected Topics in Power Electronics · 2015
Typearticle
Languageen
FieldEngineering
TopicIslanding Detection in Power Systems
Canadian institutionsUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIslandingElectrical impedanceRobustness (evolution)Electronic engineeringOvervoltageInverterDistributed generationComputer scienceFrequency bandControl theory (sociology)VoltageEngineeringElectrical engineeringTelecommunicationsBandwidth (computing)

Abstract

fetched live from OpenAlex

This paper proposes a passive islanding detection method based on computing a set of frequency-dependent reference impedance magnitudes and comparing them with the measured impedance magnitudes at the point of common coupling (PCC). The reference impedance may be identified online over a selected frequency band from the measured voltage and current at the PCC. Islanding is detected when the magnitude differences between the reference impedance and the measured impedance over the chosen frequency band are smaller than a preset threshold. Robustness of the proposed method is verified in a distribution network, the method avoids misdiagnosing islanding condition as normal condition. Performance analyses are discussed from two perspectives of nondetection zone (NDZ) and fault detection zone. By combining the undervoltage/overvoltage (UV/OV) and underfrequency/overfrequency (UF/OF) methods with the proposed method, the NDZs of UV/OV and UF/OF methods can be reduced.

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)0.001
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 score0.774
Threshold uncertainty score0.831

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.023
GPT teacher head0.267
Teacher spread0.244 · 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