Application of Hybrid GWO-BSA Technique for Resolving Multi-Objective Optimal Power Flow Problem by Incorporating Unified Power Flow Controller

Abstract The optimal power flow (OPF) is an illustrious and a substantial approach for the reliable and cost-effective working of a power system. It is a multifaceted nonlinear problem that evaluates the ideal settings of generator capacity, bus voltage, and transformer tap setting. In this study, the objectives such as minimization of fuel cost, minimization of power losses, reduction of voltage variation and augmentation of voltage stability have been solved by considering six double objective scenarios and four triple objective scenarios. The above mentioned objectives have been solved by using hybridized Grey Wolf Optimization and Backtracking Search optimization Algorithm (GWO-BSA) and by incorporating Unified Power Flow Controller (UPFC). In the multi-objective OPF problem, the Optimum Compromise Solution (OCS) is estimated by means of fuzzy set theory. For demonstrating the enactment of the hybrid GWO-BSA, simulations are performed using MATLAB on standard IEEE 30-bus and 57-bus test systems. Moreover, the comparisons have been made between the hybrid GWO-BSA and other recognized algorithms for showing the greater efficacy and robustness of the GWO-BSA against others. The comparisons divulge that the GWO-BSA offers optimal, viable, global outcomes to the OPF problems with good convergence rate.