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Record W2247274187 · doi:10.1109/epec.2015.7379948

Operation challenges of feeder shunt capacitors in islanded microgrids

2015· article· en· W2247274187 on OpenAlexaff
Nader A. El-Taweel, Hany E. Z. Farag

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsYork University
Fundersnot available
KeywordsMicrogridVoltage droopDistributed generationGridCapacitorAC powerDistributed power generationComputer scienceEngineeringLoad SheddingControl engineeringVoltageElectric power systemPower (physics)Electrical engineeringVoltage regulatorRenewable energy

Abstract

fetched live from OpenAlex

Active distribution systems are moving towards a new paradigm shift, where they can be clustered into microgrids capable of operating in both grid-tied and islanded modes depending on the penetration levels and types of the distributed generation (DG) units. Previous studies put on view lots of advantages and concerns for microgrids operation in islanded mode, whether it is initiated for emergency, intentionally planned or permanent island system purposes. One of the concerns that have not been addressed yet, is the functionality of the existing feeders shunt capacitors (FSCs) when microgrids operate in islanded mode. Hence, this paper investigates the operation conflicts between DG units and FSCs during the islanded microgrid mode of operation. These operation conflicts have been validated through conducting simulations for different local control schemes of FSCs. The results show that major voltage regulation and reactive power control problems might arise when DG units are droop-controlled and FSCs utilize conventional control schemes. Further, a new local control scheme for FSCs has been proposed to mitigate their operational challenges in islanded microgrids.

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.

How this classification was reachedexpand

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: Empirical
Teacher disagreement score0.118
Threshold uncertainty score0.234

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 head0.018
GPT teacher head0.197
Teacher spread0.178 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2015
Admission routes1
Has abstractyes

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