Research On Multi-Objective Optimal Configuration Of Distribution Network With Distributed Power Generation

With the rapid development of industry and the increasing demand for residential electricity,due to the lack of resources and serious environmental pollution of traditional power generation methods,traditional power generation methods can no longer meet the status quo.problem.At this stage,DG and traditional power generation methods complement each other and become an indispensable part of the country's construction of a smart grid.How to improve the system's ability to accept DG and maximize its grid connection function on the premise of ensuring stable operation of the distribution network It has important research significance.The dissertation starts the research work on the optimization of the distribution network with DG.The main work is summarized as follows:This thesis summarizes the research status of distribution network optimization with DG in recent years,including the model and algorithm of dealing with this problem by researchers at home and abroad,on the basis of which,the part of the existing achievements that are still insufficient is studied.This paper introduces the widely used DG,and analyzes the handling methods of different node types of DG in power flow calculation.The simulation results show that the location and capacity of DG in the distribution network is the key to the positive effect.Based on the requirements of technical indexes of distribution network,the optimization model with the minimum of network loss and static voltage stability index as the objective function is constructed.Aiming at the problem that the adaptive genetic algorithm still has the chance to fall into the local optimum in the process of solving the optimization model,the mechanism of cross mutation operator in the algorithm is improved,and the proposed algorithm is applied to the optimization model.Finally,through the analysis of an example,it shows that the algorithm has some advantages in convergence,and the minimum values of network loss and static stability index are better than the existing algorithm.Considering the importance of economic index to the operation of distribution network,a multi-objective optimization model is constructed to minimize the network loss,static voltage stability index and DG comprehensive cost.In view of the shortcomings of the existing standard immune genetic algorithm,this thesis studies an improved immune genetic algorithm,which combines the idea of immunity with the NSGA-II algorithm based on Pareto dominance relationship,and compares the performance before and after the improvement through the test function and performance index.The analysis shows that the improved immune genetic algorithm has better performance in the convergence and diversity of Pareto solution.Finally,anexample is given to show that the diversity and convergence of the improved algorithm are better,and each solution can effectively improve the optimization index,which shows the correctness and superiority of the model and algorithm in the study of distribution network optimization configuration with DG,and the Pareto solution is classified into different schemes,and the equilibrium scheme is compared with other schemes,and finally the subjective and objective conditions are obtained The recommendation scheme can satisfy the decision maker.