Research On Distribution Network Reconfiguration With Distributed Power

With the development of new energy power generation technology,higher and higher requirements are placed on the economics and reliability of distribution networks.Distributed generation(DG)has attracted more and more attention because of its positive effects of saving investment,reducing losses,diversifying energy types,etc.After DG is connected to the grid,it will cause network losses and voltage quality in the distribution network,As a result,the distribution network reconfiguration has become more complicated,making the traditional single-target distribution network reconfiguration no longer meet the needs of future distributed power generation systems.Therefore,it is of theoretical and practical engineering significance to study multi-objective distribution network reconstruction considering DG.The research work of this paper mainly includes the following aspects:Firstly,several common DGs are introduced,the impact of DG on the distribution network is analyzed,and the influence of DG output,grid connection position and its power factor on network loss is analyzed through a simplified distribution network model.Secondly,according to several typical DGs,the mathematical model in power flow calculation is established.In view of the defects of the traditional algorithm for calculating PV nodes,a forward and backward generation power flow that uses compensation and punishment strategies to correct the reactive power of PV nodes is proposed.Calculation method,and the IEEE 14 node system distribution network is used as an example to verify the correctness of the algorithm.Due to the limitations of traditional genetic algorithms in the application of distribution network reconfiguration,this paper proposes an improved genetic algorithm for the problem of multi-target distribution network reconstruction with DG,which uses non-dominated individuals based on clustering for selection.In the elite retention strategy;a part of the non-elite genes are introduced into genetic operations,and the elite individuals are crossed to produce offspring individuals.The rapid non-dominant sorting and elite retention strategies in the algorithm are improved,and the Pareto model is introduced.It meets the needs of multi-objective reconstruction and improves the distribution and diversity of Pareto optimal solutions.On the basis of the above research work,with the minimum network loss,minimum voltage offset and load balancing as the optimization goals,a reconstruction optimization model considering distribution network operation topology constraints and power flow constraints is established.Considering the economics of the network after DG is connected,the economic cost of DG is also taken as the optimization goal,and a fast non-dominated sorting genetic algorithm with elite strategy is used to solve the optimization problem of distribution network reconstruction with DG.Finally,an IEEE33 node system calculation example is used to perform simulation calculations,and analysis and comparison of the reconstruction results before and after DG grid connection reveals that the proposed network reconstruction algorithm has better diversity and distribution of Pareto optimal solutions.At the same time,it is proved that on the basis of satisfying the operation constraints of the distribution network,the DG grid optimization can reduce the network loss,improve the voltage quality,and effectively optimize the operation index of the distribution network.