A Novel Objective Function and Algorithm for Optimal PSS Parameter Design in a Multi-Machine Power System

Abstract

This paper proposes a novel objective function and algorithm to obtain a set of optimal power system stabilizer (PSS) parameters that include a feedback signal of a remote machine and local and remote input signal ratios for each machine in a multi-machine power system under various operating conditions. A novel function called the damping scale is proposed and formulated as an objective function to increase system damping after the system undergoes a disturbance. Three existing objective functions of the damping factor, damping ratio, and a combination of the damping factor and damping ratio were analyzed and compared with the proposed objective function. A novel algorithm called gradual self-tuning hybrid differential evolution (GSTHDE) was developed for rapid and efficient searching of an optimal set of PSS parameters. GSTHDE uses the gradual search concept on STHDE to enhance the probability of searching for an optimal solution. Eigenvalue analysis and nonlinear time domain simulation results demonstrated the effectiveness of the proposed objective function and algorithm.