Multi-objective Optimal Power Flow Using Biogeography-based Optimization

Abstract

Abstract This article presents a novel biogeography-based optimization algorithm for solving constrained optimal power flow problems in power systems, considering valve point non-linearities of generators. In this article, the feasibility of the proposed algorithm is demonstrated for 9-bus, 26-bus, and IEEE 118-bus systems with three different objective functions, and it is compared to other well-established population-based optimization techniques. A comparison of simulation results reveals better solution quality and computational efficiency of the proposed algorithm over evolutionary programming, genetic algorithm, and mixed-integer particle swarm optimization for the global optimization of multi-objective constrained optimal power flow problems.