Journal of Theoretical and Applied Information Technology 31 st December 2014. Vol.70 No.3 © 2005 - 2014 JATIT & LLS. All rights reserved . ISSN: 1992-8645 www.jatit.org E-ISSN: 1817-3195 482 SIMULTANEOUS COORDINATED AND TUNING OF PSS FOR A MULTIMACHINE POWER SYSTEM USING A NEW HYBRIDIZATION (GA-GR) VIA A MULTI-OBJECTIVE FUNCTION A. CHOUCHA 1,* , L. CHAIB 1,1 , S. ARIF 1,2 , L. MOKRANI 1,3 1 LACoSERE Laboratory , Amar Telidji University of Laghouat, BP 37G, Ghardaia Road – Laghouat, 03000 (Algeria) E-mail: * a.choucha@lagh-univ.dz, 1 l.chaib@lagh-univ.dz, 2 s.arif@mail.lagh-univ.dz, 3 l.mokrani@mail.lagh-univ.dz ABSTRACT This work presents a new coordinated and robust tuning procedures of power system stabilizer PSS using a novel hybridization technique to damp out power system oscillations. This hybridization is based a combination between stochastic Genetic algorithm (GA) methods and deterministic methods (gradient); it is called GA-GR, and even between themselves stochastic methods genetic algorithm and simulated annealing (GA-SA). The proposed approach is used for a multi-objective function based on the real part of eigenvalues and the damping factor, to search for optimal stabilizer parameters. To examine the effectiveness and robustness of this tuning approach in enhancing the stability of power systems, modal analysis and nonlinear simulations have been carried out on New England/New York interconnected network system 68-bus, 16-machine power system. Keywords: Genetic Algorithm (GA), Gradient Method, Modal Analysis, Power System Stabilizer, Multimachine Power System, Small Signal Stability. 1. INTRODUCTION Due to growth in electric power demand and increasing network structure Dynamic Stability problems, e.g. low frequency oscillation, become important to electric power systems [1]. Low frequency oscillations present limitations on the power-transfer capability. To enhance system damping, the generators are equipped with PSSs that provide supplementary feedback stabilizing signals in the excitation system [2]. The power systems stabilizers which are widely used for mitigating the effects of low frequency oscillation modes improve the performance and functions of power systems during normal and abnormal operations. The PSSs keep the power system in a secure state and protect it from dangerous phenomena [3]. In PSSs tuning, adjustment sequences and location are critical parameters for stabilizing optimal performance. A PSS can be adjusted to improve the damping mode. However, it can produce undesirable effects for other modes. Moreover, the various investments in of PSSs make oscillation behavior different according to the operating points. In the literature, several approaches using genetic algorithms (GA) have been proposed for coordinated and tuning of multiple power system stabilizers [4-10]. In many searches, the location of PSSs is chosen before selecting tuning methods. The participation factors (PF) method has been extensively used to identify the PSSs possible locations [10-12]. Hybridization is the result of a cross between two species, two kinds or two individuals of related species and is also a crossing of different species. In the case of optimization, the hybridization can be done between deterministic and stochastic methods and even between themselves stochastic methods. The objective of this work is to ensure an optimum coordination and tuning of PSSs. Hence, we have developed a hybrid method using GA/Gradient program for a multi-objective function And comparison between the methods of hybridization met-heuristic, based on the real part poles and the damping factor. The multi-machine power system studied consists of 16 generators and 68 nodes; it represents the New England/New York interconnected network system. 2. POWER SYSTEM MODEL