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

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.