A Cooperative Evolutionary Algorithm Based On PSO And SA For Reactive Power Optimization In Power Systems

Along with the fast increasing of population, industrialization course and transportation, the demand for energy especially electrical power has been greatly increased. The economy development will face the limit of energy bottleneck. Saving energy and reducing loss in power system is very important to building saving-style society. The balance of reactive power in the power system is the basic precondition of improving the voltage profile. The operation department of Power system faces the problem that it must take some effective control methods to reduce the transmission loss, improve the voltage profile and enhance the economics and security of the operation of power system. And it is the same important to the economic performance of the power enterprise. Reactive optimization can effectively ensure power system operation economically and securely and is one of the most important control methods to improve the voltage profile. Although there are plentiful researches and productions on the theory and application of reactive power optimization by now, difficulties still remain. Therefore study on reactive power optimization has the great significance in theory and practical application.Reactive power optimization is a mixed nonlinear programming problem with lots of variables and uncertain parameters. The operating variables include continuous variables as well as discrete variables. Therefore the optimization becomes very complex. There are two kinds of measures for reactive power optimization, classical approach and artificial intelligence approach. First, this paper introduces the research actuality of reactive power optimization, and analyses the characteristics of measures used in reactive power optimization home and abroad. According to the fast convergence performance and local convergence performance of particle swarm optimization (PSO) and global convergence performance and slow convergence performance of simulated annealing algorithm (SA) ,which are used in reactive power optimization of power system at present, a cooperative evolutionary algorithm based on SA and PSO (SAPOS) is proposed in this paper. The proposed method which combined PSO and SA efficiently makes good use of fast convergence performance of PSO and global convergence performance of SA, and can avoid efficiently falling into the local optimization. By searching in phase with PSO and SA, this algorithm can validly overcome the prematurity problem of PSO and can quicken the convergence velocity of SA.The algorithm is applied to the IEEE 14-bus system and IEEE 57-bus system, the simulation results proves that the improved method based on mix aptitude algorithm in this paper has favorable convergence precision and velocity, is effective for reactive power optimization.