Optimal reactive power flow using non dominated sorting multi objective gravitational search algorithm

Abstract

This paper presents application of non dominated sorting multi objective gravitational search algorithm (NSMOGSA) for solving optimal reactive power flow (ORPF) problems. ORPF problem is formulated as a non-linear constrained multi-objective optimization problem where different objectives and various constraints have been considered into the formulation. Fast elitist non-dominated sorting and crowding distance have been used to locate and manage the Pareto optimal front. An external archive of the Pareto optimal solutions are also used to provide some elitism. To show the efficacy of the proposed algorithm, it has been tested on a standard IEEE 30-bus system with three different individual objectives that reflect minimization of active power loss, bus voltage deviation and enhancement of voltage stability. The performance of NSMOGSA is compared with the results found by other meta-heuristic techniques reported in the recent literature. Numerical results demonstrate the tangible superiority of the proposed method in achieving the optimum ORPF solution.

Application and Comparative Analysis of Various Classical and Soft Computing Techniques for Model Reduction of MIMO Systems

“…These Pareto fronts consist of a set of non dominant solutions. The interactive fuzzy membership approach is used in deciding the compromise solution among the non dominated solutions [13].…”

“…In this paper, fuzzy membership approach [13] is used to find a best compromise solution. For the ith objective function f i of individual j can be represented by a membership function μ j i defined as:…”

“…An improved version of NSGA known as NSGA-II [11], multi-objective PSO (MOPSO) [12], multi-objective gravitational search algorithm (MOGSA) [13] are some of the latest techniques. A new weighted-sum multi-objective order reduction is suggested by Soloklo and Farsangi [14] by using harmony search algorithm.…”