Voltage stability assessment and enhancement using artificial neural networks and reactive compensation

Author

Momoh, J.A. ; Dias, L.G. ; Adapa, R.

Author_Institution

Dept. of Electr. Eng., Howard Univ., Washington, DC, USA

fYear

1996

Firstpage

410

Lastpage

415

Abstract

This paper demonstrates the use of artificial neural networks for voltage stability assessment and enhancement of a power system. The neural network is trained with data containing a variety of load patterns. The reactive compensation is applied via switchable shunt VAr support. Studies are conducted on the New England 39 bus power system. It is concluded that artificial can be used for assessment of the support needed for extending the margin, and to assess the extended stability margin with reasonable accuracy

Keywords

compensation; control system analysis computing; learning (artificial intelligence); neural nets; neurocontrollers; power system analysis computing; power system control; power system stability; reactive power control; voltage control; USA; accuracy; artificial neural networks; computer simulation; extended stability margin; load patterns; power system; reactive power compensation; switchable shunt VAr support; training; voltage stability assessment; voltage stability enhancement; Artificial neural networks; Clustering algorithms; Jacobian matrices; Load flow; Modal analysis; Power system analysis computing; Power system stability; Reactive power; Stability analysis; Voltage;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems Applications to Power Systems, 1996. Proceedings, ISAP '96., International Conference on

Conference_Location

Orlando, FL

Print_ISBN

0-7803-3115-X

Type

conf

DOI

10.1109/ISAP.1996.501108

Filename

501108