The Location and Capacity of Distributed Generation Based on Genetic Algorithm

Distributed generation (DG) has a certain impact on grid power flow, network loss, and power supply reliability when it accesses power gird. Its location directly affects operating efficiency of distribution network. The traditional location optimization algorithm is generally studied for the constant output of distributed generation. Based on the original research, a genetic algorithm based on total cost of grid operation as objective function is proposed. The algorithm simplifies and evaluates the external characteristics of the distributed generation and establishes the analysis model. The chromosome coding, crossover, mutation and other operations about distributed generation is achieved based on this implementation, and then match the genetic algorithm model. By analyzing power grid system of IEEE 33 nodes and comparing the existing research, the method proposed in this paper has been proved. This model with genetic algorithm has practical significance in reducing economic operating costs and optimizing parameters of power grid with distributed generation.