MétaCan
Menu
Back to cohort

A Study on Communication Impact in the Excitation Signal Chain of a 3-phase Synchronous Generator

2024· article· en· W4400230618 on OpenAlexaff
In Kwon Park, Dinesh Rangana Gurusinghe, Seong‐Il Kim, Yi Zhang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicPower Systems and Renewable Energy
Canadian institutionsRTDS Technologies (Canada)
Fundersnot available
KeywordsExcitationSignal generatorGenerator (circuit theory)Chain (unit)Permanent magnet synchronous generatorComputer sciencePhase (matter)SIGNAL (programming language)Electrical engineeringTelecommunicationsPhysicsEngineeringPower (physics)Voltage

Abstract

fetched live from OpenAlex

Designing of a 3-phase synchronous machine involves various constraints that depend on the size of the installation place. If the place is large enough, these constraints can be relaxed, and the generator and its associated control systems can be practically placed anywhere the design requires. However, this flexibility in the location, interface, and size of the equipment is lost when the machine has to meet certain limits of size, weight, and location for its application. Furthermore, as the modern control system becomes more advanced, it also requires more stringent environmental conditions for high performance excitation systems. Therefore, communication, usually in a digital form, is essential to connect the different parts of the excitation system. While the main field current controller, which can be a high-current thyristor bridge or something else, may still be near the machine, the communication interface allows some freedom to choose the best place for the rest of the control system. This paper explores the impact of communication channels between the components of the excitation system. It presents the proposed idea, its implementation, and the evaluation results. The results verify the validity of the communication configuration under various scenarios.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.448
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.025
GPT teacher head0.326
Teacher spread0.300 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same topicPower Systems and Renewable EnergyFrench-language works237,207