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Record W2001330753 · doi:10.1109/ccece.2010.5575128

Influence of distributed generation interface transformer and DG configurations on Temporary Overvoltage (TOV)

2010· article· en· W2001330753 on OpenAlexaff
Pouyan Saifi, Akshaya Moharana, Rajiv K. Varma, Ravi Seethapathy

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIslanding Detection in Power Systems
Canadian institutionsHydro One (Canada)Western University
Fundersnot available
KeywordsTransformerOvervoltageInverterDistributed generationVoltageEngineeringElectrical engineeringGroundDistribution transformerComputer scienceElectronic engineeringRenewable energy

Abstract

fetched live from OpenAlex

This paper presents a comprehensive analysis of the impact of Distributed Generator Interface Transformer (DGIT) configuration on Temporary Over Voltage (TOV) on the healthy phases in a distribution feeder during an unsymmetrical fault. Three common types of transformer configurations are investigated both analytically and using EMTDC/PSCAD. Subsequently, an in-depth study of the effectiveness of grounding transformer in reducing the TOVs for both rotating machine based DG and inverter based DG has been performed. All these studies have been performed on study systems with realistic system data. The results of studies presented in this paper are expected to be helpful for utilities in assessing the impact of integration of distributed generators in their system and avoiding scenarios of high TOVs.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.217
Teacher spread0.209 · 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 source (direct Gemma or distilled Codex), 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
Published2010
Admission routes1
Has abstractyes

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