Simultaneous coordinated tuning of PSSs using Artificial Fish-Swarm Algorithm

Artificial Fish-Swarm Algorithm (AFSA) is a novel method to search global optimum, which is typical application of behaviorism in artificial intelligence. This paper presents the use of AFSA as a new method for simultaneous coordinated, turning of power system stabilizers (PSSs) to enhance small-signal stability in multi-machine system. Using the linearized system model and the parameter-constrained optimization algorithm, the parameters of PSSs are tuned simultaneously. The performance of the proposed PSSs under different loading conditions is investigated. The eigenvalue analysis and the nonlinear simulation results show the effectiveness and robustness of the proposed PSSs to damp out the local as well as the inter-area modes of oscillations over a wide range of loading conditions. The method is applied for coordinated tuning of 15 PSSs in a practical system.