Optimal Power Flow Solution Using Crow Search Algorithm

摘要

This paper describes Crow Search Algorithm (CSA), inspired by the intelligent behaviour of crows to solve Optimal Power Flow (OPF) problem. CSA is a population-based method; works on behaviour of crows how to retrieve their reserve food in secrete places when the food is needed. OPF is the most familiar problem in power system optimization. The OPF problem formulation includes various constraints like generator, active power; reactive power limits and also valve point loading. The proposed method developed on the IEEE 14-bus, 30-bus and 26-bus power systems for optimize the cost of generation, emission and active power loss in single objective optimization space. The optimal results are compared to those informed in the literature. The results prove that the CSA has faster convergence and lesser cost as compared with other OPF solution methods.