Title :
Assessment of the small signal stability of the European interconnected electric power system using neural networks
Author :
Teeuwsen, S.P. ; Erlich, I. ; Fischer, A. ; El-Sharkawi, M.A.
Author_Institution :
Duisburg Univ., Germany
Abstract :
This paper deals with a new method based on neural networks for eigenvalue predictions of critical stability modes of power systems. Our special interest is focused on interarea oscillations in the European interconnected power system. The existing methods for eigenvalue computations are time-consuming and require the entire system model that includes an extensive number of states
Keywords :
eigenvalues and eigenfunctions; neural nets; oscillations; power system analysis computing; power system interconnection; power system stability; European interconnected electric power system; European interconnected power system; critical stability modes; eigenvalue computations; eigenvalue predictions; interarea oscillations; neural networks; small signal stability; Computer networks; Damping; Eigenvalues and eigenfunctions; Europe; Load flow; Neural networks; Power generation; Power system interconnection; Power system modeling; Power system stability;
Conference_Titel :
Power Engineering, 2001. LESCOPE '01. 2001 Large Engineering Systems Conference on
Conference_Location :
Halifax, NS
Print_ISBN :
0-7803-7107-0
DOI :
10.1109/LESCPE.2001.941643
