Multi-machine Power System Stabilizer Design Using Grey Wolf Optimization

This paper presents exploration of a new bio-inspired meta-heuristic technique Grey Wolf Optimization (GWO) for designing of robust and optimal Power System Stabilizer (PSS) parameters of three-machine, nine-bus Western Systems Coordinating Council Power System (WSCCPS), and the performance is noticed by comparing with Harmony Search Optimization (HSO), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) techniques based PSSs. For simultaneous control of real part of eigenvalue and damping ratio, a multi-objective function based on eigenvalue is used to die out unstable and/or lightly damped low frequency oscillations by moving them to a specific D-shape stable zone in the s-plane. The PSSs designed using HSO, PSO, GA and GWO are named as HSOPSS, PSOPSS, GAPSS and GWOPSS, respectively. The performance of designed GWOPSSs is realized by non-linear simulations, eigenvalues analysis and performance indices for different severe disturbances under various operating cases and compared with other designed PSSs. The robustness of designed GWOPSS is evaluated by testing them on unnoticed operating cases, and performance is compared with that of obtained by HSO, PSO and GA techniques. It is appeared that the GWOPSS illustrates the superior performance than other designed PSSs.