Damping Power System Oscillation Using Elitist Differential Search Algorithm in Multi Machine Power System

In this paper, damping power system oscillations is presented using the Elitist differential search algorithm (Elitist-DSA) in a multi-machine system. The tuning of power system stabilizers (PSSs) are presumed as the complex optimization problem for the security of power system. The linearized model of power system is transformed into a multimodal objective function and proposed algorithm is applied to search the best solution. Simulations are conducted in linear and non-linear models of power system to verify the robustness of proposed algorithm. Detailed comparative studies are conducted to compare the performance of Elitist-DSA based PSSs with the tuned PSSs using bacteria foraging optimization algorithm (BFOA) and particle swarm optimization (PSO) in terms of statistical analyses, improvement of eigenvalues and system damping over oscillations. The findings show the presented Elitist-DSA technique is far superior as compared to BFOA and PSO in terms of quality solution of multi-machine PSSs optimization. Thus, the proposed technique is efficient for the safety of multi-machine power system against unwanted power system oscillations.