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

fYear

2007

fDate

10-12 Oct. 2007

Firstpage

213

Lastpage

217

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/LESCPE.2007.4437381

Filename

4437381