Improvement of power system operation using a novel hybrid optimization method for optimal allocation of facts devices in radial transmission line

Abstract

This paper presents a novel hybrid heuristic algorithm, termed improved grey wolf optimization and cuckoo search optimization (IGWO-CSO), designed for multi-objective functions. This algorithm aims to optimize the allocation of flexible alternating current transmission systems (FACTS) controllers within power grids, with the objectives of minimizing active power system losses, voltage deviation, and operational costs of the system. In this research work, interline dynamic voltage restorers (IDVR) are utilized as flexible AC transmission system (FACTS) controllers. A comparative analysis is performed with other proposed heuristic optimization algorithms, including particle swarm optimization (PSO), cuckoo search optimization (CSO), grey wolf optimizer (GWO), improved grey wolf optimization (IGWO), and the combined IGWO-CSO algorithms, to confirm and validate the superiority of the proposed technique. The proposed scheme has undergone validation and has been implemented on a 30-bus IEEE electric power system. The numerical results were obtained using MATLAB. The simulation results indicate that the proposed algorithm demonstrates superior performance compared to all other algorithms in attaining the optimal global minimum solutions, characterized by the highest convergence rate