DocumentCode :
3264051
Title :
Optimization of a hybrid coordinated power system stabilizer for superconducting generator using genetic algorithm
Author :
Mayouf, F. ; Djahli, F. ; Mayouf, A. ; Devers, T.
Author_Institution :
Dept. of Electr. Eng., Univ. of Setif 1, Setif, Algeria
fYear :
2015
fDate :
10-13 June 2015
Firstpage :
1193
Lastpage :
1197
Abstract :
In this paper, the optimal tuning of a hybrid coordinated stabilizer for a superconducting generator is carried out using genetic algorithm (GA). Parameters of this hybrid stabilizer (HEGPSS), which is based on a simultaneous implementation of conventional fixed (EGPSS) and fuzzy logic (FLCEG) stabilizers in both exciter and governor systems, are adjusted using GA. The proposed approach is applied to optimize time constants and scaling factors of conventional and fuzzy coordinated stabilizers. Obtained results of a SMIB power system demonstrate the effectiveness of the proposed genetic hybrid stabilizer (GA-HEGPSS) to damp oscillations for large and small disturbances. To show its superiority, the system performance with the proposed stabilizer is compared with other stabilizers.
Keywords :
exciters; fuzzy logic; genetic algorithms; power system stability; conventional fixed stabilizers; exciter systems; fuzzy coordinated stabilizers; fuzzy logic stabilizers; genetic algorithm; governor systems; hybrid coordinated power system stabilizer; optimal tuning; scaling factors; superconducting generator; time constants; Generators; Genetic algorithms; Niobium; Optimization; Power system stability; Stability analysis; Tuning; Coordinated stabilizer; SMIB power system; fuzzy stabilizer; genetic algorithm; superconducting generator;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Environment and Electrical Engineering (EEEIC), 2015 IEEE 15th International Conference on
Conference_Location :
Rome
Print_ISBN :
978-1-4799-7992-9
Type :
conf
DOI :
10.1109/EEEIC.2015.7165338
Filename :
7165338
Link To Document :
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