Machine-learning approaches to power-system security assessment

[en] The paper discusses a framework that uses machine learning and other automatic-learning methods to assess power-system security. The framework exploits simulation models in parallel to screen diverse simulation scenarios of a system, yielding a large database. Using data mining techniques, the framework extracts synthetic information about the simulated system's main features from this database

Disciplines :

Computer science

Author, co-author :

Wehenkel, Louis ; Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation

Language :

English

Title :

Machine-learning approaches to power-system security assessment

Publication date :

September 1997

Journal title :

IEEE Expert

ISSN :

0885-9000

Publisher :

IEEE

Volume :

Issue :

Pages :

60-72

Peer reviewed :

Peer reviewed

Available on ORBi :

since 17 December 2010

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Scopus citations^®
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Bibliography

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