Comparison of Biogeography Based Optimization and Genetic Algorithm for power system damping-based controllers design

Soft computing techniques were shown to add significant advancement in solving complicated problems. They are intensively applied in optimization and the controllers design for complex nonlinear functions as well. However, different optimization techniques have wide variety of capabilities. In this work, A focus on comparing Biogeography Base Optimization (BBO) and Genetic Algorithm (GA) is shown to characterize their relative performance in optimizing controllers' parameters of a real power system. The controllers chosen are the Power System Stabilizer (PSS) and FACTS device based Power Oscillation Damper (POD). The goal of this work is to hold a generic comparison between controllers designed based on GA and BBO in the context of a multimachine system, transient short circuit fault.