Single Objective Optimal Power Flow Using Particle Swarm Optimization

Abstract

ABSTRACT Optimal Power Flow (OPF) problem in electrical power systems is considered as a static, non-linear, multi-objective or a single objective optimization problem. As the power industrial companies have been moving into a more competitive environment, OPF has been used as a tool to define the level of the inter-utility power exchange. Basically, this thesis work provides a new approach to solve the single objective OPF problem considering critical objective function of generation fuel cost minimization for utility/industrial companies, while satisfying a set of system operating constraints, including constraints dictated by the electrical network. Particle Swarm Optimization technique (PSO) has been used for this purpose. Particle Swarm Optimization (PSO) is a population based stochastic optimization technique. The system is initialized with a population of random feasible solutions and searches for optima by updating generations. The IEEE-30 bus system is considered throughout this project work to test the proposed algorithm.