Multi-objective Optimal Reconfiguration Research Of Distribution Network Based On IPSO

Distribution network is an important hub for connecting transmission lines and users.It is urgent to improve the power supply reliability and power utilization efficiency of distribution network in order to respond massive access to Distributed Generation(DG)and the development of power marketization.Distribution network reconfiguration changes the power flow distribution by changing the operating structure of the system,it is the most economical means to improve the power supply quality of the distribution network.It is valuable that multi-objective optimization reconstruction of distribution network is studied.Firstly,the theoretical basis of distribution network reconfiguration is explained,the working principle of several kinds of DG and the impact of DG on distribution network planning and power supply reliability is analyzed.The forward and backward power flow calculation is introduced,the power flow calculation model of DG is described.The advantages and disadvantages of the Particle Swarm Optimization(PSO)and the Shuffled Frog Leaping Algorithm(SFLA)are analyzed,Improve Particle Swarm Optimization(IPSO)is obtained through simplification and fusion.According to the characteristics of the distribution network operation structure,the ring-based decimal coding strategy is adopted,using ant colony random spanning tree combine with IPSO to design distribution network reconstruction strategy.Secondly,static reconstruction model of distribution network with minimum active power loss,the lowest voltage offset index and optimal feeder load balance is established.Multi-objective optimization is achieved through the Pareto dominance principle to obtain the optimal solution set,and then obtaining the standardized satisfaction degree based on fuzzy membership degree.Through Matlab simulation software,static reconfiguration simulation verification is establish based on IEEE-33 node power distribution system with DG.The results show that multi-objective optimization static reconstruction of distribution network based on IPSO can reduce active power loss and voltage offset index,and can improve load balance.Multi-objective optimization static reconstruction of distribution network based on IPSO can reduce the iteration times,and can shorten the optimization time compared to PSO.Multi-objective optimization static reconstruction model of distribution network based on IPSO has high efficiency,and can improve the power quality of the distribution network.Finally,deficiency is analyzed when Euclidean distance or Pearson correlation coefficient is as similarity measure.An improved two-layer clustering algorithm based on morphological similarity and similar amplitude is applied to load clustering,and the reconstruction period is divided according to load clustering.Dynamic reconstruction model of distribution network is established with minimum active power loss,the lowest voltage offset index,minimum feeder load balance and minimum times of switching operation.The simulation results show that the improved two-layer clustering can cluster load based on morphology and magnitude effectively and has definite anti-interference ability.Compared with static reconstruction,multi-objective optimization dynamic reconstruction of distribution network based on IPSO reduces the times of switching operation while ensures the power quality of distribution network.Multi-objective optimization dynamic reconstruction model of distribution network based on IPSO can improve power supply reliability and economy of distribution network.