TY - JFULL AU - Sidhartha Panda and N. P. Padhy PY - 2007/4/ TI - Comparison of Particle Swarm Optimization and Genetic Algorithm for TCSC-based Controller Design T2 - International Journal of Electrical and Computer Engineering SP - 550 EP - 559 VL - 1 SN - 1307-6892 UR - https://publications.waset.org/pdf/13913 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 3, 2007 N2 - Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. Since the two approaches are supposed to find a solution to a given objective function but employ different strategies and computational effort, it is appropriate to compare their performance. This paper presents the application and performance comparison of PSO and GA optimization techniques, for Thyristor Controlled Series Compensator (TCSC)-based controller design. The design objective is to enhance the power system stability. The design problem of the FACTS-based controller is formulated as an optimization problem and both the PSO and GA optimization techniques are employed to search for optimal controller parameters. The performance of both optimization techniques in terms of computational time and convergence rate is compared. Further, the optimized controllers are tested on a weakly connected power system subjected to different disturbances, and their performance is compared with the conventional power system stabilizer (CPSS). The eigenvalue analysis and non-linear simulation results are presented and compared to show the effectiveness of both the techniques in designing a TCSC-based controller, to enhance power system stability. ER -