Performance Evaluation of power system stabilizers Using Teaching Learning Based Optimization of a Multi-Machine System

Authors : Hadi DELAVARİ, Ehsan BAYAT

Pages : 2405-2411

View : 47 | Download : 22

Publication Date : 2015-05-13

Article Type : Review Paper

Abstract :Abstract. One of the main problems that lead to instability in a power system is the low frequency oscillation caused by swinging generator rotor. These disturbances cause oscillations at low frequencies that are undesirable since it affects the amount of transferred power through the transmission lines and leads to external stress to the mechanical shaft. In order to compress effectively low-frequency oscillations, a common means is to add a supplementary signal to the synchronous generator excitation system. This is the so-called power system stabilizer, PSS. The parameters of the power system stabilizer have been tuned by the two ways, particle swarm optimization (PSO) and teaching–learning based optimization (TLBO). The robustness of the proposed TLBO-based PSSs (TLBOPSS) is verified on a multi-machine power system under different operating conditions and disturbances. The results of the proposed TLBOPSS are compared with the particle swarm optimization based tuned PSS through eigenvalue analysis, nonlinear time-domain simulation and some performance indices to illustrate its robust performance for a wide range of loading conditions.
Keywords : Power System Stabilizer, TeachingLearning Based Optimization, Particle Swarm Optimization, Multi

ORIGINAL ARTICLE URL