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Using artificial neural networks to estimate rotor angles and speeds from phasor measurements
Del Angel, Alberto; Glavic, Mevludin; Wehenkel, Louis
2003
Peer reviewed
 

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Keywords :
Power Systems; Machine Learning
Abstract :
[en] This paper deals with an improved use of phasor measurements. In particular, the paper focuses on the development of a technique for estimation of generator rotor angle and speed, based on phasor measurement units, for transient stability assessment and control in real-time. Two multilayered feed-forward artificial neural networks are used for this purpose. One for the estimation of rotor angle and another for the estimation of rotor speed. The validation has been made by simulation in a power system because techniques for the direct measurement were not available. Results obtained with the help of a simple one machine to infinite bus system are presented and compared against those obtained using analytical formulas derived from the generator classical model.
Disciplines :
Electrical & electronics engineering
Author, co-author :
Del Angel, Alberto
Glavic, Mevludin 
Wehenkel, Louis  ;  Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation
Language :
English
Title :
Using artificial neural networks to estimate rotor angles and speeds from phasor measurements
Publication date :
2003
Event name :
Intelligent Systems Applications to Power Systems
Audience :
International
Peer reviewed :
Peer reviewed
Available on ORBi :
since 29 December 2010

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