Design Of Robust Pss In Multimachine Power Systems Using Dragonfly Algorithm And Jellyfish Search Algorithm

Abstract

In interconnected power system networks, due to the weak tie lines between the generators, low frequency oscillations (LFO) are introduced into the system. LFOs have been a serious concern for engineers for decades, as they cause the system to be unstable by reducing the damping torque if LFOs are not damped out rapidly. This thesis represents two new methods of modeling robust power system stabilizers (PSS) for multimachine networks using the dragonfly algorithm (DA) and jellyfish search algorithm (JSA). The proposed methods dampens LFOs by modifying the key parameters of traditional lead-leg type power system stabilizers (CPSS) using the DA and JSA optimization methods. For both models, maximizing the minimum damping ratio is considered as the objective function. These models are evaluated on a two-area four-machine network and an IEEE-39 bus network that are subject to a 3-ϕ fault. For the same networks, the results are compared to backtracking search algorithm (BSA) and particle swarm optimization (PSO). Comparative study shows that the DA and JSA based models gives better system damping performance compared to BSA and PSO optimized methods, which demonstrates that the proposed models are reliable and robust.