Title :
A neuro-fuzzy method of power disturbances recognition and reduction
Author :
Reznik, Leon ; Negnevitsky, Michael
Author_Institution :
Sch. of Commun. & Informatics, Victoria Univ., Melbourne, Vic., Australia
fDate :
6/24/1905 12:00:00 AM
Abstract :
The paper combines two major neuro-fuzzy applications in power engineering: stabilizing power systems at a generation stage and reducing disturbances at a delivery stage. It presents a neural-fuzzy classifier for recognition of power disturbances and a fuzzy excitation controller comprising both the exciter and the power system stabilizer
Keywords :
exciters; fuzzy control; fuzzy set theory; neural nets; pattern classification; power generation control; power system stability; exciter; fuzzy control; fuzzy excitation controller; generation stage; neural-fuzzy classifier; pattern recognition; power disturbance reduction; power system stabiliser; power system stability; Australia; Control systems; Frequency; Monitoring; Power engineering; Power generation; Power quality; Power system harmonics; Power systems; Steady-state;
Conference_Titel :
Fuzzy Systems, 2002. FUZZ-IEEE'02. Proceedings of the 2002 IEEE International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7280-8
DOI :
10.1109/FUZZ.2002.1006731
