Optimal location of FACTS devices using Improved Particle Swarm Optimization

In this paper a new, an Improved Particle Swarm Optimization (IPSO) is proposed for optimizing the power system performance. Recently, the Particle Swarm Optimization (PSO) technique has been applied to solve power engineering optimization problems giving better results than classical methods. Due to slow convergence and local minima, particle swarm optimization fails to give global results. To overcome these drawbacks, in this paper presents the application of improved particle swarm optimization for optimal sizing and allocation of a Static Compensator (STATCOM) and minimize the voltage deviations at all the buses in a power system. This algorithm finds an optimal settings for present infrastructure as well as optimal locations, sizes and control settings for Static Compensator (STATCOM) units. A 30 bus system is used as an example to illustrate the technique. Results show that the Improved Particle Swarm Optimization (IPSO) is able to find the best solution with statistical significance and a high degree of convergence. The simulation results are presented to show a significant improvement of the power system reliability and feasibility and potential of this new approach.

► In this paper a new, an Improved Particle Swarm Optimization is proposed (IPSO) for optimizing the power system performance.
► This paper presents an optimal sizing and location of a Static Compensator (STATCOM).
► Modeling of STATCOM included.
► IPSO is compared with GA, BFA, Benders, Branch and Bound Techniques for better results.
► It will be suitable for large scale systems.