DocumentCode :
755948
Title :
Anticipatory fuzzy control of power systems
Author :
Dash, P.K. ; Liew, A.C.
Author_Institution :
Centre for Appl. Artificial Intelligence, Regional Eng. Coll., Rourkela, India
Volume :
142
Issue :
2
fYear :
1995
fDate :
3/1/1995 12:00:00 AM
Firstpage :
211
Lastpage :
218
Abstract :
The paper presents an anticipatory fuzzy control scheme to improve the stability of electric power systems. This differs from the traditional fuzzy control in that once the fuzzy-control rules have been used to generate a control value, a predictive routine built into the controller is called for anticipating its effect on the power system output and hence updating the rule base or input-output membership functions in the event of unsatisfactory performance. The effectiveness of the anticipatory and traditional PI fuzzy controllers is demonstrated by simulation studies on a single-machine infinite-bus and multimachine power system subjected to a variety of transient disturbances for different operating conditions. The anticipatory fuzzy control, however, requires a neural network prediction routine using a modified Kalman filter-based fast-learning algorithm
Keywords :
Kalman filters; control system analysis; control system synthesis; filtering theory; fuzzy control; learning (artificial intelligence); neural nets; power system control; power system stability; power system transients; predictive control; two-term control; anticipatory fuzzy control; control design; controller; fast-learning algorithm; fuzzy-control rules; input-output membership functions; modified Kalman filter; multimachine power system; neural network prediction routine; operating conditions; performance; predictive routine; rule base; simulation; single-machine infinite-bus power system; transient disturbances;
fLanguage :
English
Journal_Title :
Generation, Transmission and Distribution, IEE Proceedings-
Publisher :
iet
ISSN :
1350-2360
Type :
jour
DOI :
10.1049/ip-gtd:19951585
Filename :
373003
Link To Document :
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