Nonlinear Time Response Optimization using Imperialist Competitive Algorithm for Tuning Robust Power System Stabilizers

In this paper, a new approach based on Imperialist Competitive Algorithm (ICA) is proposed to tune the optimal parameters of the Power System Stabilizers (PSSs) to damp the low-frequency oscillations in a multi-machine power system. The paper uses the ICA to address PSSs design problem so as to overcome the deficiency of traditional derivative-based methods and other heuristic algorithms. The main objective of this procedure is to simultaneously optimize parameters of those PSSs having fixed parameters in coping with the complex nonlinear natures of the power system. The robustness and efficiency of the newly designed stabilizers is evaluated in a New England-New York sixteen-machine power system subjected to the different operating conditions and different types of disturbances in comparison with the genetic algorithm and linear matrix inequality based PSSs design methods. The superiority of the proposed stabilizers is demonstrated through the nonlinear simulation and some dynamic performance indices studies. The results analysis reveals that the tuned ICA-PSSs have an excellent capability in damping of low frequency oscillations.