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Record W2181109213 · doi:10.1109/tpwrs.2012.2199336

Online Tracking of Voltage-Dependent Load Parameters Using ULTC Created Disturbances

2012· article· en· W2181109213 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

VenueIEEE Transactions on Power Systems · 2012
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsControl theory (sociology)VoltageTracking (education)Voltage regulationElectric power systemComputer scienceEngineeringPower (physics)Electrical engineeringControl (management)Physics

Abstract

fetched live from OpenAlex

This paper presents a field-test verified method for continuous tracking of voltage-dependent load model parameters. The basic idea is to use the natural or automatic movement of the under load tap changer (ULTC) as the source of voltage disturbance. Load parameters are estimated from each taping activity. While the idea of using manual ULTC tapping disturbances for load parameter estimation is not new, this paper has demonstrated, through laboratory tests and field measurements, that load parameters can be estimated from the automatic ULTC movements. Since a ULTC often has many movements in any given day, the load parameters can be collected in a consistent, frequent, and predictable manner and, consequently, online estimation and tracking of load parameters becomes feasible. The paper presents the implementation of the proposed method and its field measurement experiences, especially the characteristics of tap movements and the associated load responses. Experiments and a large number of field measurements presented in this paper have shown that the proposed method is a practical and effective method for determining load parameters online.

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 categoriesMeta-epidemiology (narrow)
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 score0.820
Threshold uncertainty score1.000

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 head0.030
GPT teacher head0.249
Teacher spread0.219 · 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