DocumentCode :
3508913
Title :
Learning tangent hypersurfaces for fast assessment of transient stability
Author :
Djukanovic, Wodrag ; Sobajic, Dejan J. ; Pao, Yoh-Han
Author_Institution :
Inst. ´´Nikola Tesla´´, Belgrade, Yugoslavia
fYear :
1993
fDate :
1993
Firstpage :
124
Lastpage :
129
Abstract :
A new direct method for transient security assessment of multimachine power systems is presented. A local approximation of the stability boundary is made by tangent hypersurfaces which are developed from Taylor series expansion of the transient energy function in the state space nearby a certain class of unstable equilibrium points (UEP). Two approaches for an estimation of the stability region are proposed by taking into account the second order coefficients or alternatively, the second and third order coefficients of the hypersurfaces. Results for two representative power systems are described and a comparison is made with the hyperplane method, demonstrating the superiority of the proposed approach and its potential in real power system applications. Artificial neural networks are used to determine the unknown coefficients of the hypersurfaces independently of operating conditions.
Keywords :
learning (artificial intelligence); neural nets; power system analysis computing; power system stability; state-space methods; Taylor series; applications; coefficients; learning; multimachine power systems; neural networks; power system analysis computing; state space; tangent hypersurfaces; transient energy function; transient security assessment; transient stability; unstable equilibrium points; Eigenvalues and eigenfunctions; Lyapunov method; Power system analysis computing; Power system modeling; Power system transients; Rotors; Stability; Synchronous generators; Taylor series; Transient analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks to Power Systems, 1993. ANNPS '93., Proceedings of the Second International Forum on Applications of
Conference_Location :
Yokohama, Japan
Print_ISBN :
0-7803-1217-1
Type :
conf
DOI :
10.1109/ANN.1993.264302
Filename :
264302
Link To Document :
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