MétaCan
Menu
Back to cohort
Record W2017719334 · doi:10.1080/15325000500240870

Optimal Siting of United Power Flow Controllers

2005· article· en· W2017719334 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

VenueElectric Power Components and Systems · 2005
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsUnified power flow controllerElectric power systemPower flowReduction (mathematics)EngineeringControl theory (sociology)Flexible AC transmission systemFuzzy logicPower (physics)Transmission systemVoltageComputer scienceControl engineeringTransmission (telecommunications)Control (management)Electrical engineeringMathematics

Abstract

fetched live from OpenAlex

Unified power flow controllers (UPFC) are versatile devices capable of altering flow of power in transmission systems. This article presents a simple model of UPFC and incorporates the same into the polar form of fast decoupled power flow (FDPF) algorithm. A fuzzy evolutionary programming method is proposed for optimal siting of UPFC devices with the objectives of minimizing the total operating costs and improving the system voltage profile. The dynamic data structure used in the proposed method also is presented. The proposed algorithm was tested on the IEEE 6-bus and 57-bus systems and on a 191-bus Indian system. Test results demonstrate that an optimal siting of UPFC devices will lead to a good reduction of operating costs.

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)0.000
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: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.759

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 head0.010
GPT teacher head0.199
Teacher spread0.189 · 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