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Record W2093337036 · doi:10.1109/tpwrd.2013.2283454

An Accurate Offline Phasor Estimation for Fault Location in Series-Compensated Lines

2014· article· en· W2093337036 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 Delivery · 2014
Typearticle
Languageen
FieldEngineering
TopicPower Systems Fault Detection
Canadian institutionsWestern University
Fundersnot available
KeywordsPhasorFault (geology)Electric power transmissionTransmission lineElectronic engineeringNoise (video)Electric power systemControl theory (sociology)EngineeringSeries (stratigraphy)Computer sciencePower (physics)Electrical engineering

Abstract

fetched live from OpenAlex

In series-compensated transmission lines, current and voltage signals measured by the line protection system include considerable subsynchronous frequency components (SSFCs), which are not sufficiently damped within a typical fault clearing time of the line protection system. This does not allow accurate phasor estimation and, therefore, phasor-based fault location. This paper presents an accurate algorithm which effectively filters out unwanted frequency components and noise to perform accurate phasor estimation for fault location in series-compensated transmission lines. Phasor estimation of a theoretical signal is first evaluated by using the proposed method, direct Prony analysis, and four-cycle discrete Fourier transform algorithm. Then, various fault locations of a 500-kV series-compensated transmission line simulated in PSCAD/EMTDC are used to comprehensively evaluate the performance of the proposed technique. It is shown that the proposed method can effectively attenuate SSFCs and other unwanted frequency components in current and voltage signals, allowing accurate phasor estimation to be obtained.

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 score0.722
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 communication0.0000.001
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 head0.011
GPT teacher head0.248
Teacher spread0.237 · 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