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Record W3183247188 · doi:10.1049/gtd2.12249

Overview of grounding schemes for solid‐state transformers in distribution networks

2021· article· en· W3183247188 on OpenAlexafffund
Jiajie Zang, Jiacheng Wang, Jianwen Zhang, Jianqiao Zhou

Bibliographic record

VenueIET Generation Transmission & Distribution · 2021
Typearticle
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsSimon Fraser University
FundersChina Scholarship CouncilNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsGroundTransformerComputer scienceReliability engineeringElectrical engineeringEngineeringVoltage

Abstract

fetched live from OpenAlex

Abstract Proposed to be the critical enabling component for future distribution networks, solid‐state transformers (SSTs) have drawn much attention lately. They have a massive potential to help reduce size and weight, improve efficiency, integrate microgrids, renewables and energy storages in distribution systems, and can fulfil multiple grid functions such as bidirectional power flow control, fault isolation, system reconfiguration, and post‐fault restoration. The introduction of these power electronics devices in distribution systems, however, also brings new challenges to the grid. Extra levels of electromagnetic interference, stray current, and personnel safety are among the most prominent practical issues that proper grounding arrangements can address. In this paper, considerations that should be factored into the grounding scheme design for SST ports with different voltage forms and levels are thoroughly reviewed and summarised. The characteristics of various grounding schemes used in AC and DC distribution systems are evaluated and compared in detail from different perspectives. Based on the comprehensive review, several combinations of grounding schemes are recommended for typical SSTs. In addition, the inclusion of new relay protection devices in the SST grounding scheme design, considering their characteristics and unique requirements, to enhance protection and reliability is also discussed.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.707
Threshold uncertainty score0.745

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 head0.042
GPT teacher head0.306
Teacher spread0.265 · 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 designBench or experimental
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

Citations17
Published2021
Admission routes2
Has abstractyes

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