Genetic Algorithm Based On Immune Clonal Distribution Network Reconstruction

Distribution network reconfiguration is an important means to optimize power system and important content of distribution network automation study. After analyzing the advantages and disadvantages of the clonal genetic algorithm (CGA), immune clonal genetic algorithm (ICGA), which combines CGA (Clonal Genetic Algorithm) and IA (Immune Algorithm), is proposed for distribution network reconfiguration. Immune clonal genetic algorithm (ICGA) is proposed with the concept and theory of immunity in biotic science being used for reference.Firstly, this paper analyses the significance, some common objective functions and the research actuality of the distribution network reconfiguration in this paper, and this paper also expatiates the forward/backward sweep method for distribution network power flow calculation, it lays the foundation for the next step of the research. Then according to distribution network characteristic, initial swarm, code strategy and conditions of convergence of ICGA are optimized. ICGA not only combines the advantages of CGA and IA, but also can offset the disadvantage of a single algorithm.Using IEEE standard examples, in this paper, it separately takes the minimum network loss and the maximum power reliability as the objective functions, and reconfigures the normal network and interrupted distribution network. The simulation results indicate that ICGA with application to distribution network reconfiguration can avoid slow running rate of CGA, eliminate infeasible solutions during search process, and improve convergence capability, but also have higher search efficiency and calculation rate than other methods.