In this paper, two bio-inspired meta-heuristic optimization techniques, e.g., cuckoo and harmony search optimizations, are proposed to optimally design a power system stabilizer (PSS) for a 3-machine, 9-bus Western System Coordinating Council power system. For simultaneous control of damping factor and damping ratio, an eigenvalue-based multiobjective function is explored to damp out the low-frequency oscillations from the system. The parameters of PSS are designed so that lightly and/or unstable damped mode eigenvalues are placed to a particular D-shape region in the left half of the s-plane. These optimisation techniques are used to determine PSS parameters and compared with the same parameters obtained by genetic algorithm, particle swarm optimization. The performance of all intended PSS controllers are observed, for three specific operational cases as well as unforeseen operating cases by eigenvalues analysis; non-linear simulations and performance indices, under a severe disturbance. The comparative analysis has revealed that the cuckoo search optimization based PSS design significantly improved the damping of the system.
Keywords cuckoo search optimization; genetic algorithm; harmony search optimization; low-frequency oscillations; particle swarm optimization; power system stabilizer