A Novel Power System Stabilization Technique using Advanced Genetic Algorithm Optimization Approach

In order to deal with wide range of operating environment and disturbance, Power System Stabilizers (PSS) should be developed with appropriate stabilization signals. Recently, stabilizing control techniques for the multimachine power system with the help of intelligent methods have been developed. The main aim for the stability analysis of the power system is because of the importance of the power systems in the present world. Moreover, industries do not encourage the controller design if power system stability is not significant. In order to handle the above mentioned problems, intelligent approaches are used. The optimal sequential design for multi-machine power systems is very vital and many techniques are widely used to deal with control signals in power system. Most widely used optimization technique is Genetic Algorithm (GA). But, GA takes more time in optimization and lack in accuracy. To overcome the above mentioned issues, this paper uses Non-Dominated Ranked Genetic Algorithm (NRGA) for optimization. Simulation results suggest that the proposed stabilization approach is better when compared to the conventional techniques.