DocumentCode :
3277632
Title :
A survey of the application of AI in capacitor allocation and control
Author :
Ng, H.N. ; Salama, M.M.A. ; Chikhani, A.Y.
Author_Institution :
Dept. of Electr. & Comput. Eng., Waterloo Univ., Ont., Canada
Volume :
1
fYear :
1997
fDate :
25-28 May 1997
Firstpage :
161
Abstract :
The installation of power capacitors in distribution systems yields numerous economical benefits and improvements in system performance. There are many algorithms to determine the optimal capacitor sizes and their placement in distribution systems. A majority of the research in this area has used analytical or numerical methods to determine solutions for the optimal capacitor allocation problem. With the growing popularity of artificial intelligence (AI), and availability of AI software packages, several researchers have applied AI techniques to determine optimal capacitor allocation and control. The paper is a critical survey of such techniques including neural networks, genetic algorithms, expert systems, and fuzzy set theory
Keywords :
artificial intelligence; distribution networks; expert systems; fuzzy set theory; genetic algorithms; neural nets; power capacitors; power engineering computing; artificial intelligence; distribution systems; economical benefits; expert systems; fuzzy set theory; genetic algorithms; neural networks; optimal capacitor sizes; power capacitors allocation; power capacitors control; power capacitors installation; software packages; system performance improvement; Artificial intelligence; Artificial neural networks; Availability; Genetic algorithms; Optimal control; Power capacitors; Power generation economics; Power system economics; Software packages; System performance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical and Computer Engineering, 1997. Engineering Innovation: Voyage of Discovery. IEEE 1997 Canadian Conference on
Conference_Location :
St. Johns, Nfld.
ISSN :
0840-7789
Print_ISBN :
0-7803-3716-6
Type :
conf
DOI :
10.1109/CCECE.1997.614815
Filename :
614815
Link To Document :
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