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Record W2005790804 · doi:10.1109/tpwrd.2005.852301

A Platform for Validation of FACTS Models

2005· article· en· W2005790804 on OpenAlexaff
Shan Jiang, U.D. Annakkage, A.M. Gole

Bibliographic record

VenueIEEE Transactions on Power Delivery · 2005
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsTransient (computer programming)Controller (irrigation)Control engineeringElectric power systemStability (learning theory)Power flowComputer scienceTransmission systemSIGNAL (programming language)Electronic engineeringEngineeringFlexible AC transmission systemModel validationTransmission (telecommunications)Control theory (sociology)Power (physics)Electrical engineeringControl (management)

Abstract

fetched live from OpenAlex

The paper presents a platform system for the incorporation of flexible ac transmission systems (FACTS) devices. The platform permits detailed electromagnetic transients simulation as it is of manageable size. It manifests some of the common problems for which FACTS devices are used such as congestion management, stability improvement, and voltage support. The platform can be valuable for the validation of reduced order models such as small signal or transient stability models. The paper presents details on the development and validation of a small signal based model with the inclusion of a Unified Power Flow Controller. The validated model is then used successfully for the design of a feedback controller for improved damping.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.002

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 head0.024
GPT teacher head0.223
Teacher spread0.199 · 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

Citations157
Published2005
Admission routes1
Has abstractyes

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