A Solution of Optimal Power Flow Problem in Power System Based on Multi Objective Particle Swarm Algorithm

Due to rising energy demand, the optimal power flow (OPF) has become more essential for the operation, control, and planning of power systems. The problem is formulated in the form of single-objective and multi-objective (MO) functions where a decrease of real power loss, reduction of fuel cost, and decrease of voltage deviation are considered as the objectives. in this article, a multi-objective particle swarm optimization (MOPSO) method is proposed to resolve the constrained MO OPF issue in an electrical power system with contradictory objectives. In addition, from the optimal Pareto set, the most suitable optimal solution will be extracted and given to the operator using fuzzy set theory. In order to verify the applicability and efficacy of the suggested method, the IEEE 30 bus standard system was used as a test system. The results show how the MOPSO and modified particle swarm optimization (MPSO) results are both much better than the genetic algorithms (GA) and MOGA.