New Heuristic Hybrid Algorithm for Optimal Allocation of FACTS Controllers in Power Systems

This paper presents a new methodology that integrates the Autonomous Groups Particle Swarm Optimization (AGPSO) and Grey Wolf Optimization (GWO) algorithms with multi criteria decision making methods (MCDM) to allocate the Static Var Compensator (SVC) as FACTS controllers in the electrical grids. The core purpose of FACTS devices based on the proposed hybrid AGPSO-GWO algorithm in this context are to reduce power system operating costs, voltage deviation, and real power loss. The optimization problem in this paper has been formulated as a single or multi-objective optimization problem. In this paper The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Analytical Hierarchy Process (AHP) methods have been used to identify the optimal compromise solution for the multi-objective form. Computer simulations have been established in MATLAB with an extra MATPOWER package to assess the applicability of the AGPSO-GWO algorithm on the IEEE 30 bus system. To prove the potential of the proposed algorithm, a comparability investigation with Simulated Annealing (SA) and GWO algorithms was conducted. The findings reveal that the proposed method outperforms all other approaches in terms of achieving the optimal global solution at the fastest convergence rate.