Optimal location identification of FACTS devices through genetic algorithm and the network structural characteristics techniques

In this paper, the use of techniques based on the Artificial Intelligent (AI) and the network topological structure of the power system network, for optimal location of the reactive power compensator is investigated. To determine the suitable location for the power electronics based UPFC and TCSC FACTS devices, with the proposed Network Structural Characteristics Participation factor (NSCPF), the critical mode and the associated eigenvectors of the system are found. Comparative analysis with an optimization technique of genetic algorithm (GA) to determine the optimal location, size and rating of each UPFC and TCSC FACTS devices is also carried out. All the techniques presented are tested on the IEEE 14 bus power system. The results of simulation obtained show that, the proposed NSCPF is more superior in the identification of suitable nodes for the placement of FACTS devices compared to the traditional approach of GA, as it saves time and require no iteration processes before the best location is identified.