Optimal allocation of SVC and TCSC using quasi-oppositional chemical reaction optimization for solving multi-objective ORPD problem

Abstract

This paper presents an efficient quasi-oppositional chemical reaction optimization (QOCRO) technique to find the feasible optimal solution of the multi objective optimal reactive power dispatch (RPD) problem with flexible AC transmission system (FACTS) device. The quasi-oppositional based learning (QOBL) is incorporated in conventional chemical reaction optimization (CRO), to improve the solution quality and the convergence speed. To check the superiority of the proposed method, it is applied on IEEE 14-bus and 30-bus systems and the simulation results of the proposed approach are compared to those reported in the literature. The computational results reveal that the proposed algorithm has excellent convergence characteristics and is superior to other multi objective optimization algorithms.