OPTIMAL TUNING OF POWER SYSTEM STABILIZER USING DIFFERENTIAL EVOLUTION M. AMINU, Z.O. NIYI Department of Electrical and Electronics Engineering, Federal University of Technology Yola, Adamawa State, Nigeria J. USMAN Department of Electrical and Electronics Engineering, University of Maiduguri Borno State, Nigeria and G. A. BAKARE Electrical and Electronics Engineering Programme, Abubakar Tafawa Balewa University, Bauchi, Bauchi State, Nigeria Abstract : In this paper, the problem of tuning the parameters of a Power System Stabilizer (PSS) is considered. This Problem is formulated as a nonlinear constrained optimization problem which is solved using Differential Evolution (DE). Integral of time multiplied by absolute value of error (ITAE) is taken as the objective function of optimization with the PSS parameters (gain and time constants) as the constraints. The proposed DE-PSS provides the necessary supplementary control signal to the excitation system of a generating unit represented by a single synchronous machine connected to an infinite bus. Simulation results obtained using the Matlab/ Simulink software package has confirmed the superiority of the DE-PSS over the conventional PSS in damping power system oscillations over a wide range of operating conditions. 1.0 Introduction Much effort has been invested in recent years in improving the damping performance of power systems using power system stabilizers (PSS). PSS contributes in maintaining power system stability and improving dynamic performance by providing supplementary damping signal to the excitation systems of synchronous generators used in electric power systems [1,2]. In addition, this damping is translated into an increase in power transfer capacity [3]. The most widely used stabilizer is the conventional power system stabilizer (CPSS) in which the parameter settings are fixed at certain values which are determined under a particular oper- ating condition [4,5]. Once the operating condition changes, such a stabilizer must be retuned in order to operate optimally. In recent years, a lot of researches based on Evolutionary Algorithm (EA) techniques such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Tabu Search (TS) etc have been published for tuning the PSS [6,7,8,3]. Differential Evolution (DE) is an improved version of GA for faster optimization devel- Global Jour. of Engg. & Tech. Vol. 3, No. 4, (2010) 711-717 Keywords : Power System Stabilizer, Differential Evolution, Optimization, Power System Stability