Bird Swarm Algorithm for Solving Multi-Objective Optimal Power Flow Problem

This paper applies bird swarm algorithm (BSA) to finding the solution of optimal power flow (OPF) problem. BSA is a recently developed bio-inspired evolutionary algorithm. It uses swarm intelligence derived from the social interactions and social behaviors in bird swarms for searching global optimal solution. The purpose of solving an OPF problem is to find the steady state operating point of a given network that optimizes a certain objective function. The BSA has been applied to carry out OPF for minimization of fuel cost, improvement of voltage profile, total emission cost minimization and power losses minimization. In order to show the efficacy of the proposed BSA, the standard IEEE 30-bus test systems has been selected to solve OPF problem with above mentioned objectives. The comparison of results obtained using BSA and other evolutionary computing based methods reported in the literature. It is clearly show that the proposed BSA based technique gives better result compare to other EC based techniques when solving the optimal power flow problem.