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Protection Schemes of Solid State Transformers for Different Fault Conditions

2024· article· en· W4391851521 on OpenAlexaff
Kushan Tharuka Lulbadda, Ruvini De Seram, T.S. Sidhu, Sheldon S. Williamson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicNon-Destructive Testing Techniques
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsReliability engineeringSolid-stateTransformerComputer scienceElectrical engineeringEngineeringEngineering physicsVoltage

Abstract

fetched live from OpenAlex

The idea of a Solid-State Transformer (SST) has received much interest recently and is being thoroughly explored for use in the electrical system by replacing the traditional low-frequency transformer (LFT) using high-frequency isolated ACAC conversion. The SSTs are able to offer several additional functions than the traditional LFT. As the SST concept becomes popular among the power system, the safety of the system becomes vulnerable. The SST is made of a collection of several power electronic switches which has less reliability in general. Several kinds of faults can be caused by this issue like overcurrent, overvoltage, and overtemperature. These main issues are generally discussed in this paper to give a better idea of the faults that can happen in the system due to the integration of SSTs. In order to protect the SST a specific protection scheme must be needed. Further, it must have the ability to protect the system from disturbances coursed by the integration of SST. There are several protection schemes are available in the literature for the purpose of protecting the SST. Most of them are designed based on traditional power systems which are equipped with the LFTs. A few of them are discussed in this paper with their schematic diagrams to give a better understanding. The main focus of these protection systems is the protection of power electronic switches which will discussed in detail in this paper. Therefore, this paper will be a huge benefit for the researchers who are working on designing the protection systems for SST. Further, this paper will highlight the research areas that need more focus from a protection perspective.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.021
GPT teacher head0.283
Teacher spread0.263 · 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 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

Citations3
Published2024
Admission routes1
Has abstractyes

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