Appiication Of Ant Colony And Genetic Algorithm In Reactive Power Optimize For Comparative Study

Ant colony algorithm has characteristics of fast parallel searching and be good at solving discontinuous variable combinatorial optimization problems, genetic algorithm has characteristics of global searching, widely used in optimization problem. This paper used two algorithms solving reactive power optimization problem. By making comparative study about the two algorithms in principle, performance index and practical application performance and provide a basis for choosing algorithms. In order to improve the application value of algorithms in power optimization problem, this paper introduce a kind of series hybrid algorithm based on the genetic algorithm and the ant colony algorithm, provide a new idea for improving algorithm.This paper using Ward-Hale6nodes and IEEE30nodes system and actual grid data of Qiqihar to test the two algorithms. By making comparative study about the two algorithms in convergence time, test results and optimize iteration, prove that the study of these algorithms and software is correct and effective.