Application of Biogeography-Based Optimization for Tuning Multimachine Power System Stabilizer Parameters

Abstract

Biogeography-Based Optimization (BBO) algorithm, a novel optimizing algorithm, is applied in optimal tuning of multimachine Power System Stabilizer (PSS) parameters. The tuning of fixed-structure lead-lag type PSS parameters is formulated as a quadratic performance optimization problem. An eigenvalue-based objective function is chosen to maximize the damping ratio of the electromechanical modes at different system operating conditions. BBO algorithm, robust to the initial solution and computationally efficient compared with other meta-heuristic algorithms, such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Evolutionary Strategy (ES), is employed to search for optimal PSS parameters. Simulations are carried out on two typical multimachine power systems. Both frequency-domain eigenvalue analysis and time-domain dynamic simulation verify the effectiveness and robustness of the proposed BBO based PSSs under a wide range operating conditions. Moreover, the superiority of the proposed BBO algorithm is further illustrated by algorithm optimization performance evaluation and dynamic response damping characteristic compared with GA, PSO and ES. Keywords: Biogeography-Based Optimization (BBO), electromechanical oscillations, multimachine power system, parameter optimization, Power System Stabilizer (PSS).