Abstract:
Abstract—in this paper, a Multi-Objective Particle Swarm optimization (MOPSO) technique is proposed for
solving the Optimal Power Flow (OPF) problem in a deregulated environment. The OPF problem is formulated
as a nonlinear constrained multiobjective optimization problem where the fuel cost and wheeling cost are to be
optimized simultaneously. MVA-km method is used to calculate the wheeling cost in the system. The proposed
approach handles the problem as a true multiobjective optimization problem. The results demonstrate the
capabilities of the proposed approach to generate true and well-distributed Pareto-optimal solutions of the
multiobjective OPF problem in one single run. In addition, the effectiveness of the proposed approach and its
potential to solve the multiobjective OPF problem are confirmed. IEEE 30 bus system is considered to
demonstrate the suitability of this algorithm.
