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Record W2012801064 · doi:10.1109/psamp.2006.285379

Distributed Generation Micro-Grid Operation: Control and Protection

2006· article· en· W2012801064 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 institutionsUniversity of Waterloo
Fundersnot available
KeywordsTrippingIslandingGridReliability (semiconductor)Computer scienceInverterScheme (mathematics)Automatic frequency controlReliability engineeringElectric power systemControl (management)Distributed generationControl engineeringEngineeringVoltagePower (physics)Electrical engineeringRenewable energyCircuit breakerTelecommunications

Abstract

fetched live from OpenAlex

Performing intentional islanding or micro-grid operation of Distributed Generators (DGs) can improve the power system service quality and increase the power system reliability. Despite the benefits micro-grid operation can bring to the power system, many challenges and technical issues constraint its operation. This paper addresses two main challenges associated with the operation of micro-grids: voltage/frequency control and protection. The main aim of this paper is three-fold. First, a control strategy for inverter based DGs is proposed to control both voltage and frequency during islanded operation. Secondly, a protection scheme is proposed to protect both the lines and DGs during islanded operation. Lastly, both the control scheme and the protection scheme are coordinated to avoid nuisance tripping of the DGs and non-critical loads. The study is performed using a digital computer simulation approach PSCAD/EMTDC.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.870
Threshold uncertainty score0.294

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 head0.006
GPT teacher head0.170
Teacher spread0.164 · 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

Citations169
Published2006
Admission routes1
Has abstractyes

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