PSO-Based Optimal Design of a Neuro-Sliding Mode Controller for the Transient Stability Enhancement of Multimachine Power Systems with UPFC

摘要

In recent years, the novel population based particle swarm optimization (PSO) algorithm has been gaining importance in solving optimization problems. In this paper, a PSO-based neuro-sliding mode controller has been proposed for the transient stability enhancement of multimachine power systems with unified power flow controller (UPFC). The UPFC is modeled as controllable loads at the buses where it is installed. The controllable parameters of the UPFC are obtained using a sliding mode control (SMC) strategy. A PSO-based single neuron controller is proposed to adapt the parameters of the sliding mode controller. The efficacy of this new approach in damping the local-mode and inter-area mode of oscillations is confirmed by comparing the transient performance with that of a conventional proportional-plus-integral (PI) controller and that of a neuro-sliding mode controller without PSO technique. Several computer simulation results on a two-area four-machine twelve-bus power system are presented to show the marked improvement in transient stability enhancement over a wide range of operating conditions.