New genetic-fuzzy controller for improving stability of superconducting generator with high response excitation in a SMIB power system

Author

Mayouf, F. ; Djahli, F. ; Mayouf, A. ; Devers, T.

Author_Institution

Dept. of Electr. Eng., Univ. of Setif 1, Setif, Algeria

fYear

2013

fDate

1-3 Nov. 2013

Firstpage

330

Lastpage

335

Abstract

As continuity of our previous published works dealing with improving transient stability of the superconducting generator with high response excitation (SGHRE), we have introduced in this paper fuzzy logic controllers (FLC) in the excitation and governor loops. In order to obtain optimal values of normalization and de-normalization factors, a genetic algorithm has been used (GFEG). Non-linear simulation results of SMIB, under different operating conditions, have demonstrated the effectiveness of the proposed stabilizer GFEG.

Keywords

control system synthesis; electric generators; fuzzy control; genetic algorithms; machine control; power system transient stability; superconducting machines; FLC; GFEG; SGHRE; SMIB power system; denormalization factor; excitation loops; fuzzy logic controller; genetic algorithm; governor loops; nonlinear simulation; single machine connected to infinite bus; superconducting generator with high response excitation; transient stability improvement; Generators; Genetic algorithms; Mathematical model; Niobium; Power system stability; Stability analysis; Superconducting magnetic energy storage; Fuzzy logic stabilizer; Superconducting generator; genetic algorithm; high response excitation;

fLanguage

English

Publisher

ieee

Conference_Titel

Environment and Electrical Engineering (EEEIC), 2013 13th International Conference on

Conference_Location

Wroclaw

Print_ISBN

978-1-4799-2802-6

Type

conf

DOI

10.1109/EEEIC-2.2013.6737931

Filename

6737931