Title :
Mid and Long-Term Voltage Stability Assessment using Neural Networks and Quasi-Steady-State Simulation
Author :
Assis, T.M.L. ; Nunes, A.R. ; Falcão, D.M.
Author_Institution :
Fluminense Fed. Univ. (UFF), Niteroi
Abstract :
This paper presents a methodology to estimate voltage stability margin using artificial neural networks (ANN). During the training process, a quasi-steady-state (QSS) simulator is used, so the slow dynamic devices, which are important in the voltage stability assessment, are adequately modelled. The results obtained for a test system have shown the potential benefits of the proposed methodology and the importance of considering slow dynamic aspects when the voltage stability margin is to be calculated.
Keywords :
neural nets; power engineering computing; power system security; power system simulation; power system transient stability; neural networks; quasi-steady-state simulation; quasi-steady-state simulator; slow dynamic device; training process; voltage stability assessment; Analytical models; Artificial neural networks; Neural networks; Power system analysis computing; Power system dynamics; Power system modeling; Power system security; Power system simulation; Power system stability; Voltage; Voltage stability assessment; artificial neural networks; quasi-steady-state simulation;
Conference_Titel :
Power Engineering, 2007 Large Engineering Systems Conference on
Conference_Location :
Montreal, Que.
Print_ISBN :
978-1-4244-1583-0
Electronic_ISBN :
978-1-4244-1583-0
DOI :
10.1109/LESCPE.2007.4437381