This paper presents an efficient and reliable evolutionary-based approach to solve the optimal
power flow (OPF) problem. To search the optimal setting of control variables for the OPF, which
is formulated as a nonlinear constrained objective optimization problem with both equality and
inequality constraints, particle swarm optimization (PSO) algorithm is used. The standard IEEE
30-bus power system is studied to illustrate how the proposed method has an efficient role. The
objectives are minimizing the total fuel cost, system power loss, installation cost of FACTS and
voltage profile improvement. Two different types of FACTS devices are incorporated with the test
system, SVC and UPFC, to achieve the objective functions under certain constraints. Furthermore,
the proposed method is used to determine the optimal location of FACTS controller. The results
show the effectiveness of UPFC with optimal settings over the SVC under the same conditions.
Also, the results illustrate the importance of determination of the best location of FACTS devices.