Optimal Design of Power System Stabilizers using a Small Population Based PSO
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Abstract
Power system stabilizers (PSSs) are used to generate supplementary control signals to excitation systems in order to damp out local and inter-area oscillations. In this paper, a modified particle swarm optimization (PSO) algorithm with a small population is presented for the design of optimal PSSs. The small population based PSO (SPPSO) is used to determine the optimal parameters of several PSSs simultaneously in a multi-machine power system. In order to maintain a dynamic search process, the idea of particle regeneration in the population is also proposed. Optimal PSS parameters are determined for the power system subjected to small and large disturbances. The effectiveness of the PSSs parameters determined by the SPPSO algorithm is observed in damping out the power system oscillations fast after a disturbance. The advantage of the proposed approach is its convergence in fewer evaluations and lesser computations are required per evaluation. Results obtained with the SPPSO optimized PSSs parameters are compared against published PSS parameters for the Kundur''s two area power system.
