Coordinated tuning of the parameters of PI, PSS and POD controllers using a Specialized Chu–Beasley's Genetic Algorithm

Abstract

This paper presents a Specialized Chu–Beasley's Genetic Algorithm (SCBGA) to perform coordinated tuning of the parameters of proportional-integral and supplementary damping controllers (power system stabilizers and interline power flow controller-power oscillation damping) in multi-machine electric power systems. The objective is to insert additional damping to low frequency electromechanical oscillations. The current sensitivity model was used to represent the system, therefore all of its devices and components were modeled by current injection. A novel current injection model for the interline power flow controller is presented and a static analysis is considered to validate it. The New England test system – consisting of 10 generators, 39 buses, and 46 transmission lines, divided into two areas with both local and inter-area oscillation modes – was used for the simulations. The SCBGA was compared to other five algorithms: a Random Search, a Local Search, a Simulated Annealing, a Genetic Algorithm, and a Particle Swarm Optimization method, in terms of performance for the tuning of the parameters of the controllers. The results demonstrated that the SCBGA was more efficient than these other techniques. In addition, the obtained solutions proved to be robust when variation of the loads was considered.