Title :
Development of adaptation methods of fuzzy logic power system stabilizers
Author :
Voropai, N.I. ; Etingov, P.V.
Author_Institution :
Energy Syst. Inst., Irkutsk
Abstract :
This paper presents an adaptive fuzzy logic power system stabilizer (FLPSS). A two-stage technology of FLPSS adaptation is considered taking into account real conditions in a bulk electric power system. A genetic algorithm (GA) is applied for tuning parameters of FLPSS. An artificial neural network (ANN) is used on-line to adapt the FLPSS to changes in operating conditions
Keywords :
fuzzy logic; genetic algorithms; neural nets; power engineering computing; power system stability; ANN; adaptation methods; artificial neural network; bulk electric power system; fuzzy logic; genetic algorithm; power system stabilizers; tuning parameters; Artificial intelligence; Artificial neural networks; Fuzzy logic; Fuzzy systems; Genetic algorithms; Power system modeling; Power system stability; Power system transients; Power systems; Tuning; Artificial Neural Network; Fuzzy Logic; Genetic Algorithm; Power System Stabilizer; Power system stability;
Conference_Titel :
Power Engineering Society General Meeting, 2006. IEEE
Conference_Location :
Montreal, Que.
Print_ISBN :
1-4244-0493-2
DOI :
10.1109/PES.2006.1709101
