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Record W2154642422 · doi:10.1049/iet-rpg.2009.0031

Probabilistic evaluation of transient stability of a power system incorporating wind farms

2010· article· en· W2154642422 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

VenueIET Renewable Power Generation · 2010
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsTransient (computer programming)Electric power systemFault (geology)Control theory (sociology)Context (archaeology)TurbineWind powerProbabilistic logicTime domainEngineeringStability (learning theory)Computer sciencePower (physics)Reliability engineeringElectrical engineeringPhysics

Abstract

fetched live from OpenAlex

This study presents a stochastic-based approach to evaluate the probabilistic transient stability indices of a power system incorporating wind farms (WFs). In this context, investigations have been conducted on a hypothetical test system representing a typical power system taking into consideration the uncertainties of the factors associated with the practical operation of a power system, namely fault type, fault location, fault impedance, fault clearing process, system parameters and operating conditions and high-speed reclosing process. The effects of the WF sizes and locations on the overall system stability have been investigated. Moreover, this study presents stochastic models for the wind turbine as well as the spring constant of the reduced two-mass shaft model of the wind generator. The time-domain simulations are obtained using the electro-magnetic transient programme.

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)0.003
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.238
Threshold uncertainty score0.760

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.021
GPT teacher head0.226
Teacher spread0.205 · 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