Optimal Placement and Parameter Sizing of Unified Power Flow Controller using Meta-Heuristic Techniques

Abstract

This paper presents the comparative study of various meta-heuristic optimization techniques like the Cuckoo Search Algorithm (CSA), Ant Colony Optimization (ACO) & Particle Swarm Optimization (PSO) to examine the optimal placement and parameter sizing of the unified power flow controller (UPFC) in IEEE 30 bus system. The objective functions of this study are the reduction of the fuel cost and UPFC installation cost. The optimization problem is solved using MATLAB R2016a and GAMS software. The result of the study shows the effectiveness of Cuckoo Search Algorithm and superior performance than ACO and PSO in finding out the optimal placement and parameter sizing of the UPFC.