Optimal Site and Parameters Setting of UPFC Based on Hybrid Genetic Algorithm for Enhancing Loadability

Unified Power Flow Controller (UPFC) is one of the most useful Flexible AC Transmission Systems (FACTS) devices for rising loadability of power system by minimizing the overloaded lines and the bus voltage violations. However, to what extent the act of UPFC can be brought out, it highly depends upon the site and the parameters setting of this device in the system. The optimal placement and the optimal parameters setting of UPFC for increasing loadability are determined by means of a niche hybrid genetic algorithm (HGA). This genetic algorithm is a modified method for global optimization. It provides a new architecture of hybrid algorithms, which organically merges the niche techniques and Nelder–Mead’s simplex method into genetic algorithms (GAs). To verify our proposed approach, we perform simulations on IEEE 14-bus power system and the results are compared to Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) in term on speed and accuracy of convergence. The results indicate that HGA, GA and PSO can successfully achieve the proper settings and placement of UPFC but the HGA is faster than other mentioned algorithms.