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A FUZZY VARIABLE STRUCTURE CONTROLLER FOR TRANSIENT STABILITY ENHANCEMENT OF FLEXIBLE AC TRANSMISSION SYSTEM

2006· article· en· W1998698215 on OpenAlexvenueno aff
P.K. Dash, M. H. Naeem

Bibliographic record

VenueInternational Journal of Power and Energy Systems · 2006
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsnot available
Fundersnot available
KeywordsControl theory (sociology)Electric power systemRobustness (evolution)Fuzzy logicTransient (computer programming)Unified power flow controllerVariable structure systemEngineeringController (irrigation)Variable structure controlFlexible AC transmission systemControl engineeringComputer scienceSliding mode controlPower (physics)Power flowPhysicsNonlinear systemControl (management)

Abstract

fetched live from OpenAlex

This article presents the design of a new fuzzy variable structure controller for the unified power flow controller (UPFC) in a multimachine power system. This new design provides overall variable proportional and integral gain in damping both inter-area and local modes of oscillations of the synchronous generators in multimachine power systems. The conventional PI controllers that are used to adjust the series converter voltage and phase angle of the UPFC show inferior performance compared to the proposed controller for a variety of transient disturbances covering faults and power changes. The conventional integral control along with a variable structure fuzzy proportional control scheme based on a sliding surface and its derivative provides a superb steady-state performance as well as dynamic performance that damps the system oscillations rapidly. The sliding surface also provides robustness against any uncertainty in the system parameters and disturbance modes.

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)0.000
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 score0.970
Threshold uncertainty score0.455

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 head0.005
GPT teacher head0.200
Teacher spread0.195 · 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

Citations1
Published2006
Admission routes1
Has abstractyes

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