A NOVEL APPROACH TO SOLVING THE OPTIMAL POWER FLOW PROBLEM BASED ON PARTICLE SWARM OPTIMIZATION

This paper presents an efficient and reliable evolutionary-based algorithm to solve the Optimal Power Flow (OPF) problem of electric power systems. The proposed algorithm employs the concept of swarm behavior in finding the optimum (e.g., food source) in nature, called Particle Optimal Swarm (PSO). The problem is to determine the set-point of the power system, including the power output of generators, the voltage of PV bus, etc., to supply the demand at least cost, at the same time subject to the equality and inequality constraints of the system. The algorithm was successfully tested in a 5-bus system and the simulation result showed its robustness and effectiveness compared to the conventional method in literature