POWER SYSTEM STABILIZATION USING MODEL PREDICTIVE CONTROL BASED ON IMPERIALIST COMPETITIVE ALGORITHM

This paper presents a hybrid method based on Generalized Predictive Control (GPC) and Imperialist Competitive Algorithm (ICA) for simultaneous coordinate design of two Power System Stabilizers (PSSs) to damp the multi-machine power system low frequency oscillations. A sequential linearized model predictive controller based on the GPC is designed and an efficient ICA algorithm is proposed for optimizing the cost function of GPC. The numerical results are presented on a 2-area 4-machine power system. To show the effectiveness of the designed PSS, a line-to-ground fault and a three phase fault are applied. Also, to compare the results obtained by ICA, the Genetic Algorithm (GA) is applied, too. Furthermore, the GPC algorithm is applied for comparison. Simulation results show the superiority and capability of the proposed stabilizers to enhance the power system damping over the other methods.