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Record W2765860318 · doi:10.1115/1.4038342

The Coordinated Immersion and Variance Control of Power Systems With Excitation and Steam-Valve

2017· article· en· W2765860318 on OpenAlex

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

VenueJournal of Dynamic Systems Measurement and Control · 2017
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsLakehead University
FundersDistinguished Middle-Aged and Young Scientist Encourage and Reward Foundation of Shandong ProvinceNational Natural Science Foundation of ChinaMinistry of Education of the People's Republic of ChinaNational Science Foundation
KeywordsControl theory (sociology)Lyapunov functionNonlinear systemElectric power systemBoiler (water heating)Controller (irrigation)Transient (computer programming)Computer scienceControl engineeringEngineeringPower (physics)Control (management)Physics

Abstract

fetched live from OpenAlex

Transient stability is the key problem for reliable and secure planning under the new deregulated market conditions. By using immersion and invariance (I&I) method, a nonlinear coordinated generator excitation and steam-valve controller is designed to improve transient stability of power systems. The proposed coordinated I&I controller can assure power angle stability, voltage, and frequency regulations, when a large disturbance occurs on the transmission line or a small perturbation to mechanical power. Compared with the Lyapunov method, the proposed method does not need to construct a Lyapunov energy function. Some numerical simulations are used to validate the proposed controller. Simulation results show that the nonlinear coordinated I&I controller has better control performance than the existing coordinated passivation controller (CPC).

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)0.002
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: none
Teacher disagreement score0.682
Threshold uncertainty score0.370

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.007
GPT teacher head0.192
Teacher spread0.185 · 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