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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 OpenAlexaff
S.O. Faried, R. Billinton, S. Aboreshaid

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.

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)0.001
metaresearch head score (Gemma)0.006
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: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.021
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

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
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

Citations73
Published2010
Admission routes1
Has abstractyes

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