Conceptual designs of AI-based systems for local prediction of voltage collapse

Author

Yabe, K. ; Koda, J. ; Yoshida, K. ; Chiang, K.H. ; Khedkar, P.S. ; Leonard, D.J. ; Miller, N.W.

Author_Institution

Tokyo Electr. Power Co. Inc., Japan

Volume

11

Issue

1

fYear

1996

fDate

2/1/1996 12:00:00 AM

Firstpage

137

Lastpage

145

Abstract

Vulnerability of modern power systems to locally initiated voltage collapse gives rise to a need for methods to measure local voltage security and to predict voltage instability. The paper presents a novel architecture based on a suite of AI technologies and three-dimensional PQV surfaces which provides prediction of local voltage collapse and indices of system voltage security. Robustness and adaptation are demonstrated on difficult and realistic power system simulation models

Keywords

artificial intelligence; fuzzy systems; inference mechanisms; power system analysis computing; power system measurement; power system security; power system stability; voltage measurement; AI technologies; artificial intelligence; fuzzy Kalman filter; inference module; load prediction; local voltage collapse prediction; local voltage security measurement; neuro-fuzzy system; power system simulation models; three-dimensional PQV surfaces; Artificial intelligence; Power measurement; Power system measurements; Power system modeling; Power system protection; Power system reliability; Power system security; Power system simulation; Power system stability; Voltage measurement;

fLanguage

English

Journal_Title

Power Systems, IEEE Transactions on

Publisher

ieee

ISSN

0885-8950

Type

jour

DOI

10.1109/59.485995

Filename

485995