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A Practical Method to Represent Distance Protection Relays in Transient Stability Simulations of Lines Connecting Inverter-Based Resources

2023· article· en· W4387027444 on OpenAlexaff
Óscar Acevedo Patiño, Carolina Correa Soto, Ahda P. Grilo, Rodrigo A. Ramos, Renan M. Furlaneto, Ilhan Koçar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower Systems Fault Detection
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsTransient (computer programming)Stability (learning theory)ConvertersInverterComputer scienceSoftwarePower (physics)Fault (geology)Electric power systemPower-system protectionProtective relayElectronic engineeringReliability engineeringEngineeringElectrical engineeringVoltage

Abstract

fetched live from OpenAlex

In this paper, it is proposed the use of a method for accurately representing distance protective relays models in stability simulations of power systems with inverter-based resources (IBR). Typical distance relays may fail to protect lines with IBRs due to the response of the converters during a fault. Consequently, different schemes have been proposed in the literature to improve the distance relays performance in the presence of IBRs and they should be properly represented in stability simulations. Considering the difficulty in modeling these unconventional protection schemes in stability software programs, this paper combines the use of a stability software and a short-circuit program to accurately represent the distance protection model in stability simulations. Simulations using a power system with a high wind power share are used to validate the method.

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 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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.594
Threshold uncertainty score0.454

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.066
GPT teacher head0.340
Teacher spread0.274 · 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 teacher head, 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

Citations1
Published2023
Admission routes1
Has abstractyes

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