Research On Multi-objective Optimization Strategy For Distribution Network Congestion Scheduling Considering Electric Vehicle Charging Load

Under the background of increasing power supply contradiction between power generation side and demand side,energy shortage and increasing environmental protection,research on green energy supply and energy use technology has become a hot spot of social concern.As a new type of transportation,electric vehicles are widely concerned by the government and society because of their zero pollution to the environment,high energy efficiency,and safety and economy.Considering the factors driven by the government and the continuous development of technology,electric vehicles in the future occupy a very important position in people’s travel.Based on the hysteretic charging control model of electric vehicles,this paper studies the charging control and regulation technology of large-scale electric vehicles,eliminates the congestion phenomenon of distribution network caused by centralized charging,and utilizes the flexible adjustable and controllable characteristics of electric vehicles to respond to the upper-level power grid adjustment commands and achieve the goal of auxiliary distribution network operation.The main research contents of this paper are as follows:Firstly,based on the existing hysteretic charging control model of electric vehicles,this paper studies an optimal energy state regulation control strategy suitable for the orderly charging of large-scale electric vehicles.Based on the power density distribution function of the electric vehicle cluster,the optimal adjustment amount of the electric vehicle energy state is determined.Then,based on the optimal energy state regulation control strategy,this paper discusses the impact of changes in its related control parameters on its response effect,and combines power distribution network flow analysis to verify the improvement of the strategy on system network loss and voltage level.Secondly,in order to further explain the response effect of the optimal energy state adjustment amount control strategy,this paper proposes the concept of relative state of charge and designs a relative state of charge demand response strategy based on the parameter serialization idea.The electric vehicles are sorted according to the relative state of charge,and the number of electric vehicles participating in demand response control is determined according to the response target power.The examples in this paper compare the response effects of the two strategies from three aspects: response speed,response accuracy,and user satisfaction,to further verify the effectiveness of the strategy.Finally,this paper proposes a multi-objective optimization strategy for distribution network congestion dispatch from the perspectives of optimizing the benefits and costs of the power dispatching center,electric vehicle aggregators,and electric vehicle users to achieve the lowest operating cost or maximum benefit for each stakeholder.In order to eliminate the congestion of the distribution network caused by disorderly charging of electric vehicles in the cluster,a blocking price adjustment strategy is proposed in this paper.The grid dispatch center collects a certain blocking fee based on the power draw of the congestion line by the electric vehicle aggregators.In order to reduce expenditures,companies will optimize the charging behavior of electric vehicles in their jurisdictions to minimize congestion costs.