Power system operation enhancement using a new hybrid methodology for optimal allocation of FACTS devices

Abstract

The proposed research article introduces a new hybrid heuristic algorithm based on Autonomous Groups Particle Swarm and Grey Wolf optimizers (AGPSO-GWO) via multi-objective function for the allocation of the Flexible Alternating Current Transmission Systems (FACTS) controllers in power grids to minimize the active power system losses, voltage deviation, and the system operational costs. In this research work, the Static Var Compensator (SVC), Thyristor-Controlled Series Compensator (TCSC), and Unified power flow controller (UPFC) are used as FACTS controllers. A comparative analysis is conducted with other proposed heuristic optimization algorithms such as Particle Swarm Optimization (PSO), Autonomous Group Particle Swarm Optimization (AGPSO) Grey Wolf optimizer (GWO), and improved grey wolf optimization (IGWO) algorithms to confirm and validate the superiority of the proposed technique. Moreover, the proposed AGPSO-GWO has been compared with the previous existing Simulated Annealing (SA) in the literature to prove its superiority and ensure its validity. The proposed scheme has been validated and applied on 30-bus and 118-bus IEEE electric power systems. The numerical results had been carried out using MATLAB and MATPOWER packages. The simulation results show that the proposed algorithm offers the best performance among all algorithms to achieve the optimum global minimum solutions with the highest convergence rate.