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Record W4387684298 · doi:10.6113/tkpe.2023.28.5.377

Validity Study of foreign Technical Standards for Frequency-Based Synthetic Inertia Through Analysis of Wind Turbines and Power System Dynamics

2023· article· en· W4387684298 on OpenAlexaboutno aff
Ye-Chan Kim, Seung-Ho Song

Bibliographic record

VenueThe Transactions of the Korean Institute of Power Electronics · 2023
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsnot available
Fundersnot available
KeywordsInertiaWind powerDynamics (music)GridPower (physics)Computer scienceEngineeringEnvironmental scienceControl engineeringElectrical engineeringMathematicsPhysics

Abstract

fetched live from OpenAlex

This study investigated the foreign technical standards for synthetic inertia and evaluated the validity of the Hydro-Québec technical standards through power system simulations. By referencing the ENTSO-E technical document and the Hydro-Québec grid code, we summarized the synthetic inertia parameters and their minimum values. By including a wind farm with Hydro-Québec

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)0.008
metaresearch head score (Gemma)0.044
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: Methods · Consensus signal: none
Teacher disagreement score0.047
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.044
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.246
Teacher spread0.235 · 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
GenreMethods

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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