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Record W4385521694 · doi:10.1109/tpwrd.2023.3301555

Impact of Inverter-Based Resources on Different Implementation Methods for Distance Relays—Part II: Reactance Method

2023· article· en· W4385521694 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 · 2023
Typearticle
Languageen
FieldEngineering
TopicPower Systems Fault Detection
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsReactanceInverterGridComputer scienceMeasure (data warehouse)EngineeringVoltagePhase (matter)Electronic engineeringReliability engineeringElectrical engineeringMathematicsData mining

Abstract

fetched live from OpenAlex

Part I of this article investigated the performance of distance relays that use phase comparators in systems with inverter-based resources (IBRs). Part II investigates distance relays that are based on the reactance method, another common technique used in existing relays. Similar to Part I, the IBRs in this article comply with the low-voltage ride-through requirements of recent grid codes (including the generation of negative-sequence current), and the relays measure a combination of IBR and load currents. This article will examine if the basic assumptions of the reactance method hold under such scenarios. In addition to theoretical analysis, the article will also present case studies that indicate the differences between the impacts of IBRs on the reactance method and the previously discussed phase comparators, hence the need for separate treatment of the reactance method. The findings of this article are corroborated using PSCAD/EMTDC 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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.671
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
Bibliometrics0.0000.001
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 head0.024
GPT teacher head0.353
Teacher spread0.329 · 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