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Record W4413394433 · doi:10.1109/tcst.2025.3599206

An Explicit Direct Method for Transient Stability Analysis of Multimachine Power Systems With Nonzero Transfer Conductances

2025· article· en· W4413394433 on OpenAlexfundno aff
Jianli Gao, Balarko Chaudhuri, Alessandro Astolfi

Bibliographic record

VenueIEEE Transactions on Control Systems Technology · 2025
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsnot available
FundersOntario Ministry of Research and InnovationEngineering and Physical Sciences Research Council
KeywordsTransient (computer programming)Control theory (sociology)Stability (learning theory)Transfer (computing)Maximum power transfer theoremTransient analysisElectric power systemPower (physics)MathematicsComputer sciencePhysicsTransient responseEngineeringControl (management)ThermodynamicsArtificial intelligenceElectrical engineering

Abstract

fetched live from OpenAlex

We propose an explicit analytical direct method for the transient stability analysis of multimachine power systems with nonzero transfer conductances (TCs). The proposed method addresses two issues. In the first issue, we study the transient stabilization of the entire power system through excitation control design. To this end, a globally well-defined Lyapunov function is constructed, and a locally well-defined dynamic passivity-based control law is proposed. The closed-loop equilibrium is therefore guaranteed to be locally asymptotically stable. In the second issue, we study the transient stability property of post-fault initial states. To this end, an optimization-based approach to calculate the critical level set of the proposed Lyapunov function is proposed. This allows to estimate an explicit region of attraction of the closed-loop equilibrium. Therefore, the transient stability property of a post-fault initial state can be directly assessed. A case study on the IEEE 10-machine 39-bus power system, to demonstrate the performance and effectiveness of the proposed direct method, is presented.

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 score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.009
GPT teacher head0.256
Teacher spread0.247 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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