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Record W1922828617 · doi:10.1109/sedst.2015.7315270

Challenges of modeling electrical distribution networks in real-time

2015· article· en· W1922828617 on OpenAlex
Paul Forsyth, Onyinyechi Nzimako, Cyprian Peters, Mohamed Moustafa

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venue2015 International Symposium on Smart Electric Distribution Systems and Technologies (EDST) · 2015
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsRTDS Technologies (Canada)
Fundersnot available
KeywordsComputer scienceBandwidth (computing)Variety (cybernetics)Distributed computingDistributed generationTask (project management)Electronic engineeringElectrical engineeringTelecommunicationsEngineeringSystems engineeringRenewable energy

Abstract

fetched live from OpenAlex

This paper describes the challenges associated with real time modeling of electrical distribution networks. Distribution networks are tightly coupled electrically which makes it more difficult to model them using parallel processing techniques. Power electronic devices and distributed energy resources are continually increasing the complexity of distribution networks and consequently the task of simulating them in real time is more difficult. Detailed and accurate models need to be made available to represent distribution loads as well as protection and control equipment. In addition, a wide variety of communication protocols with significant bandwidth are required. Finally the trend to apply Power Hardware in the Loop simulations to test distribution equipment is a challenge in of itself.

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.

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: Empirical
Teacher disagreement score0.250
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 studies0.0000.000
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 head0.016
GPT teacher head0.238
Teacher spread0.222 · 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