With Distributed Power Distribution Network Planning Based On Genetic Algorithm

Rapid economic growth led to the industrial progress, improve the quality of our national life, followed by the growth of energy consumption and power consumption. Growing power load of electric power system flexibility, reliability, further deepened, the influence of network loss and environmental pollution problems are also gradually appear, obviously, relying on traditional energy sources, relying on the existing power system cannot meet the requirements of users on the quality of power supply and power supply reliability. DG technology (Distributed Generation, DG) after this concept proposed, effectively solves the problem of energy shortage and environmental pollution of the electric power industry, for reasonable utilization of resources, reduce environmental pollution has opened up a new way. In the area of a DG is involved in power generation, the user of electricity from DG and power plant, DG and electricity network coexistence phenomenon., this phenomenon will affect the electricity network tide flow, system stability, and power quality, in addition, the introduction of a large number of DG will make the system sensitivity, and degree of complexity increases significantly. So, it is necessary to reasonable power network planning including DG, to improve power supply reliability, flexibility, balance of supply and demand, reduce environmental pollution, to make full use of distributed energy, and complementary to the grid coordinate, and realize the sustainable development of energy and reasonable use, the power industry.This paper combined with the characteristics of DG introduces what is the classification and current situation of the development of distributed power supply and distributed power supply. Secondly, this paper introduces the basic methods of traditional electric power network planning optimization, planning and use of classical network from the aspects such as different and influence of the electric power network planning including DG, the meter and these effects, covering many constraints, multi-objective programming model is established; Again, the DG active efforts are not sure this characteristic analysis, combined with the principle of statistics, use the software to simulate the active output; Finally, the application of genetic algorithm to solve the model, get a set of relatively complete planning scheme.