Research On The Distributed Network Reconfiguration With The Distributed Generation

With the continuous development of the national economy and the continuous progress of industrialization, power users of the city continue to increase and the rapid development of distributed power supply, we need to put some new requirements for distribution network.Bearing capacity of distribution network for the new load and consumption of distributed power supply is a problem worthy of attention. Reconstruction of the distribution network is an important means to improve the power quality, load balancing network reliability and reduce system loss. However, due to the increase of the power system load with its uncertainty and access of distributed power supply, given the traditional distribution network reconfiguration important influence, therefore it is necessary to have depth study in the distribution network which contain distributed power but with uncertain load.In order to analyze DG distribution network reconfiguration problem more better, this paper on the overall consideration of the system active power loss, the minimum balance of base load and voltage deviation,established a distribution network comprising DG reconfigurable multi-objective optimization model.. On this basis, the lower semi linear membership function for the objective function for processing, using maximum satisfaction for multi-objective reconfiguration are analyzed, including DG multi-objective distribution network reconfiguration is converted into a single objective optimization problem based on fuzzy theory. In the distribution network reconfiguration optimization process, first introduced the basic principle of FA and the variable neighborhood search algorithm, on this basis, in view of the global firefly algorithm of traditional search ability and rapid, but the local exploitation ability is weak and other shortcomings, proposes a hybrid intelligent optimization algorithm of firefly algorithm and local search ability of variable domain the combined search. Two examples were used in the paper in order to compare the model and the algorithm. firstly, compared the result of distribution network with the access of DG and the result without the access of DG to verify the effect of DG. Besides, verified the the superiority of firefly algorithm when compared to other intelligent optimization algorithm.algorithm proposed in this paper and the original firefly algorithm and improved particle swarm algorithm are compared, the proposed method is verified through examples of good practicability and adaptability, practical significance and verification the proposed model.Because of that the wind, PV and load is random, we put some new requirements for the reconfiguration of distribution network. In this paper, in the condition of given DG and a probability load density function, applied point estimation method to deal with uncertain information, and then set up the calculation method of the random flow of distribution network. Based on the stochastic trend, considering the randomness of DG load, the multi-objective optimization problem for annual energy production and distributed power generation loss minimum reconfiguration of distribution network is proposed in this paper,using the firefly-variable domain algorithm, considering the influence of load fluctuation on the reconstruction of the distribution network, and then according to the cumulative distribution function and probability density function of node voltage distribution network reconfiguration in this paper to evaluate the effect of model. Finally, through the actual examples, we can verify the influence of the uncertain information for reconfiguration of distribution network and also verify the validity of the method proposed in this paper and the simulation.