Title :
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
fDate :
2/1/1996 12:00:00 AM
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;
Journal_Title :
Power Systems, IEEE Transactions on
