Genetic Algorithm Applied To Optimization Of Reactive Power System

Biology is development through two basic processes: natural selection and zoogamy. To adapt the change of environment, biology have been evolved by genetic,variation and nature wash out.Genetic Algorithm is a randomization search method. The main characteristic of it is the colony search game and the information change of the individual in the colony. The search independent of the grads, robust ,astringency; and its currency is better, hasn't the differentiability; the process of bed into the optimized problem is simple. It don't need the deep realize of the problem. So it is very applied to the complicated, nonlinear problem that the tradition search method difficult to resolve. It is very fit for the computer operation.This paper made some improvement to the simple GA. The Simulated Annealing Algorithm is import into the simple GA. The genetic algorithm with annealing selection improves the optimized performance of the simple GA, so that delay the selected press effectively.And then this paper studies the development of GA ( genetic algorithm ), the improvement of GA and the application of GA in the power system. The topics discussed include GA design, GA improvement, and optimal design of power system.After that, the genetic algorithm with annealing selection is used in the reactive power optimization in distribution network. The mathematical model is established, which is fit for practical application, the summation of active power losses is least; voltage beyond limits and capacitor investment is the least. The mended measures are used in IEEE 6, and IEEE 30 nodes distribution network and the results indicate that these improvements are propitious to optimization of reactive power compensation.