A multiobjective tuning approach of power system stabilizers using particle swarm optimization

Abstract

This work presents an optimal tuning approach of power system stabilizers (PSSs) using multiobjective particle swarm optimization. Two types of PSSs are investigated, the conventional speed-based PSS type and a dual-input PSS type that uses the accelerating power as an additional input. The tuning problem of these PSSs is formulated as a minimization problem of a vector objective function characterizing the damping and the transient performance of the closed-loop system. A 3-machine 9-bus power system example is considered, and the speed-constraine multiobjective particle swarm optimization algorithm is used to solve the optimization problem. The results show that trade-offs exist between the 2 objective functions of the problem, and that the best trade-off is obtained with the dual-input PSS. The performance of the resulting PSSs is illustrated through numerical simulations considering different scenarios.