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Control Systems Testing with a Flexible Co-simulation Interface to PSCAD/EMTDC

2022· article· en· W4352980696 on OpenAlexaff
Ashwin Damle, O.B. Nayak, A.M. Gole, Ajinkya Sinkar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPython (programming language)Scripting languageInterruptComputer scienceCo-simulationInterface (matter)Embedded systemSoftwareInterpreterMicrocontrollerModelSimOperating systemGraphical user interfaceField-programmable gate arrayProgramming languageVHDL

Abstract

fetched live from OpenAlex

This paper discusses a general-purpose co-simulation interface to a non-real-time electromagnetic transient (EMT) simulation software called PSCAD. The interface uses embedded Python interpreter which supplements the EMT capabilities with powerful mathematical functions and scripting facilities. The co-simulation is demonstrated with an example of controls implemented in Python running on a personal computer (PC) as well as the same controls running on a Raspberry Pi Pico microcontroller via an interrupt-based processor-in-loop (PIL) version of the interface. The PIL platform allows for rapid development, validation, testing, and prototyping of the control algorithm on a hardware platform. The paper presents the advantages of performing PIL co-simulation using a powerful scripting language such as Python embedded into an EMT simulation. It includes comprehensive details of the interface along with controller source code to help readers implement it. The power systems example used to demonstrate the interface is a boost converter implemented in PSCAD.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.876
Threshold uncertainty score0.591

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.017
GPT teacher head0.250
Teacher spread0.232 · 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 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

Citations1
Published2022
Admission routes1
Has abstractyes

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