MétaCan
Menu
Back to cohort
Record W4400318865 · doi:10.23977/jeeem.2024.070204

Strategy and Practice of Power System Relay Protection under Extreme Weather Conditions

2024· article· en· W4400318865 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Electrotechnology Electrical Engineering and Management · 2024
Typearticle
Languageen
FieldEngineering
TopicPower Systems and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsRelayExtreme weatherPower (physics)MeteorologyEnvironmental scienceGeographyClimate changeGeologyOceanographyPhysics

Abstract

fetched live from OpenAlex

With the continuous expansion and increasing complexity of the power system, the protection requirements for the power system are also increasing. Although traditional relay protection systems can play a certain protective role, they have some limitations, such as the inability to comprehensively monitor the power system and the lack of accurate judgment. Developing and applying intelligent relay protection systems has become an important way to improve the safety and reliability of power systems. This article explored the relay protection strategies and practices for power systems under extreme weather conditions. Traditional relay protection systems have limitations in addressing the increasingly complex protection needs of power systems. Therefore, the development and application of intelligent relay protection systems have become a key way to improve the safety and reliability of power systems. This article verified the effectiveness of the knowledge base based relay protection fault handling process in improving the safety, stability, and fault handling efficiency of power systems through experimental results and discussions. The experimental results showed that under different fault conditions, the processing accuracy was generally high, and in the vast majority of cases, the accuracy exceeded 90%. For example, the accuracy of handling line short circuits and voltage anomalies was 95% and 96%, respectively.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.857
Threshold uncertainty score0.535

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.209
Teacher spread0.200 · 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