The Immune Algorithms And Its Application In Power Distribution System Planning

Distribution network is the final part of the whole power system which faces the customers directly, with the continuous development of social economics in our country. The distribution network is more and more important. The Distribution network optimal planning is a complex and multi-aspect problem, in which much mathematical knowledge involved, which get more and more attention from electricity companies and researchers. This paper conducted a in-depth study for The planning of distribution network, proposing the model of immune algorithms to solve this problem, which has certain theoretical value and the value of application.Distribution network optimal planning consists of many specific problems, such as load forecasting, substation optimal planning, feeder optimal planning and switch location planning, this paper is mainly discussing the feeder optimal planning, including its modeling, coding method and algorithm, using the excellent ability of solving the multi-objective planning problem, the immune algorithm synthetically take the build charge, the net waste, and the reliability into account.In the process of introducing immune algorithm into distribution net planning, I proposed a new coding method for distribution net planning named reverse Prufer coding method, which change the phenomena that the traditional 0,1 coding method brings too much unfeasible solution which leading the algorithm can not go on, it fills the gaps of traditional coding method. When decoding the reverse Prufer code, it will meet the distribution net running need, which is that the net is a radiate tree. In the course of evolution, there is no unfeasible solution, so this coding method improves the speed of convergence and efficiency.Concentration control, distilling and inoculating vaccine is the main difference between immune algorithms and genetic algorithms. This paper researched the characteristic of reverse Prufer code, and then concretely brought forward the method of vaccine distilling and inoculating, which accelerate the breed of better pattern, which result in improving the speed of convergence.Finally, my work is focus on working out the program of immune algorithms, using the toolbox of gads in Matlab7, this work is enjoyably. By contrast immune algorithms with genetic algorithms, the former is more feasibility and validity.