Optimal Tuning of Multimachine Power System Stabilizer using Cuckoo Search Algorithm

Abstract

In this paper, optimal multiobjective design of robust multimachine Power System Stabilizers (PSS) using Cuckoo Search (CS) optimization algorithm is presented for small-signal stability enhancement. This algorithm is based on the obligate brood parasitic behaviour of some cuckoo species in combination with Lévy flight behaviour of some birds and fruit flies. A conventional speed-based lead-lag PSS is used in this work. The parameters of the Cuckoo Search based Power System Stabilizer (CSPSS) are optimized simultaneously to shift the unstable or poorly damped electromechanical mode eigenvalues of all operating conditions to a D-shape zone in the left half of the s-plane. A multiobjective eigenvalue based objective function is designed to optimize a problem involving the damping factor and damping ratio of the electromechanical modes. To show the effectiveness and the robustness of CSPSS, time domain simulations, eigenvalue analysis and performance indices are presented and compared with Genetic Algorithm based PSSs (GAPSS) and Particle Swarm Optimization based PSO (PSOPSS) under wide range of operating conditions and severe disturbances. It is observed that CSPSS exhibits improved damping performance compare to GAPSS and PSOPSS.