Optimization of PSS4B Based on Hybrid Particle Swarm Optimization

Abstract

With the rapid development of power system, the power grid becomes more and more complex, which makes the system often appear low frequency oscillation. PSS is the most important measure to suppress low-frequency oscillations, but the single-branch PSS is difficult to meet the requirements of the current power system, most of the applications of PSS4B with superior performance to suppress low-frequency oscillations. In this paper, the mechanism of low frequency oscillation and common PSS model are introduced. Secondly, the hybrid particle swarm optimization algorithm with higher convergence accuracy is improved based on the basic particle swarm optimization algorithm. Finally, based on the infinite motor system, the simulation results of three systems without PSS, with PSS4B and optimized PSS4B were compared by setting different disturbances. The simulation results show that PSS4B parameter simulation optimized by hybrid particle swarm optimization algorithm can suppress the oscillation faster and enhance the stability of the system.