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Voltage Sag Reduction at Sunnybrook Health Sciences Center Using a Digital Twin Simulation

2025· article· W4416286699 on OpenAlexaffabout
Sean D. Budhooram, Vijay K. Sood, Ting Ma, Dave Simmons

Bibliographic record

Venuenot available
Typearticle
Language
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsSunnybrook Health Science CentreOntario Tech University
Fundersnot available
KeywordsVoltage droopReduction (mathematics)Voltage sagBlackoutMode (computer interface)MATLABVoltagePower (physics)

Abstract

fetched live from OpenAlex

A joint project between Sunnybrook Health Sciences Center, Ontario Tech University, ELCYN and MITACS was launched to create a “digital twin” replica of the Sunnybrook Bayview Campus grid-tied electrical system with onsite power generation. The model was created in MATLAB Simulink and served as the basis for sandbox environment testing of experimental modes of co-generator control to reduce severity of frequent grid-sided voltage sags. After tuning the model, DROOP mode was implemented in the co-generator for testing and showed promising results in terms of system voltage stability.

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 categoriesMeta-epidemiology (narrow)
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 score0.606
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0010.001
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 head0.023
GPT teacher head0.300
Teacher spread0.277 · 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.

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
Published2025
Admission routes2
Has abstractyes

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