Chitara, DhanrajSinghal, P.K.Surana, S.L.Sharma, GulshanBansal, Ramesh C.2024-01-252024-01-252024-01Chitara D., Singhal P.K., Surana S.L. et al. 2024, 'Robust multi-machine power system stabilizer design using bio-inspired optimization techniques and their comparison', International Journal of Electrical Power and Energy Systems, vol. 155, art. 109615, pp. 1-19, doi : 10.1016/j.ijepes.2023.109615.0142-061510.1016/j.ijepes.2023.10961http://hdl.handle.net/2263/94100DATA AVAILABILITY : Data will be made available on request.This paper reports a comparative study among four bio-inspired meta-heuristic techniques i.e. Sooty-Tern Optimization (STO), Grey Wolf Optimization (GWO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) to tune the robust Power System Stabilizer (PSS) parameters of the multi-machine power system. These approaches are successfully tested on two bench-mark systems: sixteen-machine, sixty-eight-bus New England Extended Power Grid (NEEPG) and three-machine, nine-bus Western System Coordinating Council (WSCC). The efficacy of planned PSS via STO and GWO is validated by extensive non-linear simulations, eigenvalue analysis, and performance indices for numerous operating conditions under decisive perturbations, and outcomes are matched with those of GA and PSO techniques. In addition, the robustness is also tested for these algorithms. The results indicate that the PSS design using STO and GWO improves the small-signal stability and damping performance for mitigating inter-area and local area modes of low-frequency oscillations compared to GA and PSO.en© 2023 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.Particle swarm optimization (PSO)Genetic algorithm (GA)Sooty-Tern optimization (STO)Grey Wolf optimization (GWO)Power system stabilizer (PSS)New England extended power grid (NEEPG)Western System Coordinating Council (WSCC)Low-frequency oscillationsSDG-07: Affordable and clean energyArticle