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Constant-Parameter VBR Synchronous Machine Model for Studies of Unbalanced Faults in PSCAD

2024· article· en· W4394995349 on OpenAlex
Rahul Raman Ramesh, Taleb Vahabzadeh, Juri Jatskevich

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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsConstant (computer programming)Computer scienceControl theory (sociology)Synchronous motorEngineeringElectrical engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Faults and unbalanced operation of generators in power systems require appropriate models in electromagnetic transient (EMT/EMTP-type) simulation programs used for system studies. Therefore, it is essential to have computationally efficient models of synchronous machines that can also predict the unbalanced conditions and generator protection operation that is often realized by monitoring the neutral circuit current. The so-called constant-parameter voltage-behind-reactance (CP-VBR) machine models have recently been introduced for widely used nodal-analysis-based EMTP simulators as computationally advantageous alternatives to the traditional qd0 models. This paper advances the previous work and generalizes the CP-VBR model to include the floating neutral point by extending the equivalent conductance matrix that is used for interfacing within the EMTP solution. The new model is implemented in the PSCAD/EMTDC program and is demonstrated to have advantages over the built-in traditional qd0 model in studies with unbalanced faults.

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)0.000
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 score0.806
Threshold uncertainty score0.381

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 head0.023
GPT teacher head0.279
Teacher spread0.256 · 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

Quick stats

Citations4
Published2024
Admission routes1
Has abstractyes

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