MétaCan
Menu
Back to cohort
Record W3171084863

Simulation Model of Solid-state Transfer Switch for Power Transfer Performance Evaluation

2020· article· en· W3171084863 on OpenAlexaff
A.Z. Arsad, Siti Nur Fatinah, M. S. Abd Rahman, Pin Jern Ker, Md. Abdus Salam

Bibliographic record

VenueJournal of Energy and Environment · 2020
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Launch and Propulsion Technology
Canadian institutionsWestern University
Fundersnot available
KeywordsThyristorFault (geology)VoltageMaximum power transfer theoremMATLABTransfer (computing)Controller (irrigation)Transfer functionPower (physics)Control theory (sociology)Computer scienceElectric power systemTransformation (genetics)EngineeringElectronic engineeringAutomotive engineeringElectrical engineeringControl (management)
DOInot available

Abstract

fetched live from OpenAlex

This paper addresses the use of thyristors based solid-state transfer switches (SSTS) systems to increase efficiency power flows in medium-voltage distribution. Detail of SSTS in electric distribution systems modelling was demonstrated in graphical diagrams using MATLAB/SIMULINK. Circuit test at specific fault condition was carried out to verify the system side fault and prove the functionality of the proposed SSTS system for sensitive loads. The used controller based on the Park’s transformation for performing fast transfer between two feeders were demonstrated. Results of the proposed SSTS control system which monitors the voltage and current source employed fast load switching between two distribution feeders. It is observed that SSTS was evaluated under fault showed the fast detection and transfer time during the operation.

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)0.000
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: none
Teacher disagreement score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.001

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 head0.013
GPT teacher head0.204
Teacher spread0.191 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Energy and EnvironmentSame topicElectromagnetic Launch and Propulsion TechnologyFrench-language works237,207