DocumentCode :
2500145
Title :
Small signal stability assessment and control of power systems
Author :
Mirfendereski, S. ; Wahab, Noor Izzri Abdul ; Jasni, J. ; Othman, M.L.
Author_Institution :
Dept. of Electr. & Electron. Eng., Univ. Putra Malaysia, Serdang, Malaysia
fYear :
2012
fDate :
6-7 June 2012
Firstpage :
515
Lastpage :
520
Abstract :
A method for assessment and control of small signal stability (SSS) has been proposed in this paper. As the angle of rotor represents the stability of the system, the proposed method tries to assess the instability and its solutions by using comparison instead of time consuming conventional method. The idea divides power networks into different areas. The system has sub-controllers and main controller with different authorities which will results in fast and reliable prediction and control of SSS. Artificial intelligence could be used as a tool that would give the ability of learning to the system which gives the system the opportunity to response fast and accurate in future problems.
Keywords :
learning (artificial intelligence); power engineering computing; power system control; power system stability; SSS prediction reliability; artificial intelligence; power system control; rotor angle; small-signal stability assessment; system stability; Control systems; Eigenvalues and eigenfunctions; Equations; Power system dynamics; Power system stability; Stability criteria; Artificial Intelligence; Assessment of Instability preventive control; Rescheduling; Small Signal Stability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Engineering and Optimization Conference (PEDCO) Melaka, Malaysia, 2012 Ieee International
Conference_Location :
Melaka
Print_ISBN :
978-1-4673-0660-7
Type :
conf
DOI :
10.1109/PEOCO.2012.6230920
Filename :
6230920
Link To Document :
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