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Record W1849868204 · doi:10.1109/drpt.2000.855634

New approach for static VAr compensator controller design

2002· article· en· W1849868204 on OpenAlexaff
C. Y. Chung, C.T. Tse, CM Cheung, Carol Yu, K.W. Wang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsUniversity of Alberta
FundersChina Scholarship CouncilHong Kong Polytechnic University
KeywordsControl theory (sociology)Static VAR compensatorLead–lag compensatorSensitivity (control systems)Constraint (computer-aided design)ModalController (irrigation)Mode (computer interface)InstabilityComputer scienceEngineeringControl engineeringVoltagePhysicsElectronic engineeringAC powerControl (management)Materials science

Abstract

fetched live from OpenAlex

A systematic approach for static VAr compensator (SVC) design is proposed. The choice of SVC location and damping signal are based on both modal and sensitivity analyses. As the SVC instability is detected in the design process, the design (structure and setting) is achieved through a combined sensitivity coefficient (CSC) which automatically takes into account the damping of both the interarea and SVC modes. The setting is said to be optimal when the CSC with respect to all damping controller parameters approach zero. It is shown that if the SVC mode constraint is ignored, tuning the lead/lag settings for interarea mode damping alone can actually lead to adjustment in the wrong direction.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.472
Threshold uncertainty score0.999

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)0.0010.000

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 head0.046
GPT teacher head0.217
Teacher spread0.171 · 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.

Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations3
Published2002
Admission routes1
Has abstractyes

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