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Record W3134460430 · doi:10.1109/tpwrs.2021.3062906

Emulating Synchrophasor Frequency Measurements With Transient Stability Simulation

2021· article· en· W3134460430 on OpenAlexafffund
Zhen Dai, Joseph Euzebe Tate

Bibliographic record

VenueIEEE Transactions on Power Systems · 2021
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhasorTransient (computer programming)Frequency domainControl theory (sociology)ComputationPhasor measurement unitStability (learning theory)Electric power systemComputer scienceUnits of measurementReal Time Digital SimulatorFrequency responseElectronic engineeringEngineeringAlgorithmPower (physics)Electrical engineering

Abstract

fetched live from OpenAlex

In transient stability simulators such as PSS/E, the bus frequency is estimated using a window of (positive-sequence) phasor angle measurements. A digital filter is often used to account for the filtering effect in actual measurement devices and to eliminate sudden changes during frequency computations. Although transient stability simulators label the filtered angle derivative as the “frequency,” the frequency provided by such programs does not match actual measurements reported by phasor measurement units (PMUs), which makes it difficult to gauge the validity of studies (e.g., wide-area event detection and control applications) that are based on such simulations. In this paper, we implement a frequency computation method directly using positive phasor angles provided by simulators. The proposed method is tested on two systems extensively and validated against the measurements of an actual PMU. The improved frequency measurements closely match PMU responses. Cross-validation results also suggest the method may be used for other systems without conducting full time-domain simulations.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.033
GPT teacher head0.236
Teacher spread0.203 · 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

Citations5
Published2021
Admission routes2
Has abstractyes

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Same venueIEEE Transactions on Power SystemsSame topicPower System Optimization and StabilityFrench-language works237,207