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Record W2617818448 · doi:10.1049/iet-gtd.2016.2005

Structure preserving energy function including the synchronous generator magnetic saturation and sub‐transient models

2017· article· en· W2617818448 on OpenAlexaff
Mohamed Ramadan Younis, Reza Iravani

Bibliographic record

VenueIET Generation Transmission & Distribution · 2017
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTransient (computer programming)Saturation (graph theory)Permanent magnet synchronous generatorGenerator (circuit theory)Control theory (sociology)Transient analysisEnergy (signal processing)Computer sciencePhysicsTransient responseMathematicsEngineeringElectrical engineeringVoltagePower (physics)ThermodynamicsArtificial intelligence

Abstract

fetched live from OpenAlex

This study presents, develops and evaluates a structure preserving energy function based on the sixth‐order generator model which is formulated with respect to the centre‐of‐inertia. Flux saturation and leakage flux effects are also included in the model. Each load is represented as voltage‐dependent load. It is demonstrated that the proposed energy function satisfies the energy function required conditions. This study also derives a modified energy function from the original development which provides a simpler representation with less computational need while preserving the same accuracy. Physical interpretation of each term of the modified energy function is also discussed. To evaluate and verify the accuracy of the modified energy function, the critical clearing time using potential energy boundary surface method and the time‐domain simulation results of a test system are presented. The calculation of the critical energy based on the proposed energy function differs by at least 10% (more accurate) compared with the existing energy functions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.209
Teacher spread0.193 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2017
Admission routes1
Has abstractyes

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