Bio-inspired Algorithms for the Design of Multiple Optimal Power System Stabilizers: SPPSO and BFA
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Abstract
Power System Stabilizers (PSSs) provide stabilizing control signals to excitation systems to damp out inter-area and intra-area oscillations. The PSS must be optimally tuned to accommodate the variations in the system dynamics. Designing multiple optimal PSSs is a challenging task for researchers. This paper presents the comparison between two bio-inspired algorithms: a Small Population based Particle Swarm Optimization (SPPSO) and the Bacterial Foraging Algorithm (BFA) for the simultaneous tuning of a number of PSSs in a multi-machine power system. The cost function to be optimized by both algorithms takes into consideration the time domain transient responses. The effectiveness of the algorithms is evaluated and compared for damping the system oscillations during small and large disturbances. The robustness of the optimized PSSs in terms of damping is shown using the Matrix Pencil analysis.
