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Record W4243513260 · doi:10.32920/ryerson.14653656

A Novel Hybrid Active Anti-Islanding Method For Multi-Converter Fed Distributed Generation Systems

2021· preprint· en· W4243513260 on OpenAlex
Sasan Mostafaei

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
Typepreprint
Languageen
FieldEngineering
TopicIslanding Detection in Power Systems
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsIslandingSynchronizingConvertersAC powerDistributed generationControl theory (sociology)Computer sciencePower (physics)Electronic engineeringFrequency deviationPhotovoltaic systemRenewable energyAutomatic frequency controlEngineeringVoltageElectrical engineeringTelecommunicationsControl (management)Physics

Abstract

fetched live from OpenAlex

This thesis presents a novel active anti-islanding detection scheme for the three phase gridconnected converters. The proposed hybrid method works based on the combination of Positive Feedback Frequency Shift (PFFS) and Reactive Power Variation (RPV) methods, and therefore it combines the features of both methods. Unlike the RPV scheme, this method is capable of synchronizing all power converters with each other in a distributed generation (DG) system. Therefore, it can effectively detect islanding when the DG system has multiple renewable energy sources interfaced to the system by multiple converters. The proposed method can also be combined with other active methods, such as the active frequency drift method. This minimizes the power quality degradation since the scheme is called upon only when 0.1Hz deviation in the grid frequency is detected. Moreover, unlike other positive feedback methods, this scheme has little impact on the stability of the DG system, since the positive feedback reference is only limited to

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.926
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.050
GPT teacher head0.290
Teacher spread0.240 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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