A coordinated genetic based type-2 fuzzy stabilizer for conventional and superconducting generators

This paper presents a new coordinated genetic interval type-2 fuzzy stabilizer for enhancing stability of a single machine infinite-bus (SMIB) power system including conventional or superconducting generators. Its principle is based on a coordination done by implementing simultaneously, interval type-2 fuzzy controllers, into excitation and turbine governor systems. Optimal adjustment of scaling factors has been carried out using genetic algorithms (GAs). Type-2 fuzzy controller provides improvement in comparison with type-1 controller in terms of modeling and minimizing the effect of uncertainties. Furthermore, governor control helps in damping oscillations enhancement especially in case of superconducting machine when excitation control alone is not sufficient. Non-linear simulation results of a SMIB power system, under different operating conditions, prove the effectiveness and the robustness of the proposed optimized type-2 fuzzy stabilizer (GFLC2EG) for both conventional and superconducting generators. In order to validate the robust performance of the proposed stabilizer, a comparative study is presented showing its superiority over other types of stabilizers.