و استفاده از آن در حل مسايل بهينه سازي سيستمهاي قدرت P.S.O معرفي الگوريتم

An Introduction to Particle Swarm Optimization Algorithm and its Application to Power System Problems

Optimal management and planning of resources in a power system is one of the most important branches in this field. A survey on this topic shows that conventional mathematical optimization methods such as lagrangian method, decent gradient, Newton method... are well developed to solve optimization problems used in a power system. Depend on these procedures, first or second derivatives of the cost function respect to control variables should be evaluated to find the best direction of movement toward optimal point. However in such a case in which cost function is not differentiable or discrete variables are used to represent an objective function, mathematical based algorithms are usually failed to find the best solution. This paper introduces a new heuristic based algorithm entitled Particle Swarm Intelligence method and examines its capability to power system application. Simple structure and basic rules of this procedure makes it suitable for solving power system optimization problems. In comparison with other methods, P.S.O has a good and acceptable rate of convergence. Consequently in the next stage of this paper three different kinds of objective functions applicable into a power system are introduced and the best solution of this constrained optimal power flow is evaluated and the results are compared with those given by genetic algorithm.