No abstract

This paper describes optimal power flow based on swarm intelligences in which the power transmission loss function is used as the problem objective. Although most of optimal power flow problems involve the total production cost of the entire power system, in some cases some different objective may be chosen. In this paper, to minimize the overall power transmission losses, four decision variables are participated. They are i) power generated from generating plants, ii) specified voltage magnitude at control substations, iii) tap position of tap changing transformers and iv) reactive power injection from reactive power compensators. Swarm intelligences are wellknown and widely accepted as potential intelligent search methods for solving such a problem. In this paper, Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC) and Differential Evolution (DE) are employed to solve optimal power flow problems. A 6-bus and 30-bus IEEE power systems are used for test. As a result, all swarm intelligences search algorithms can solve optimal power flow problems efficiently. The artificial bee colony and the differential evolution provide results better than other swarm intelligent techniques.