Aggregated Pricing Method For Electric Vehicle Charging Load Considering Group Price Response

In order to achieve the "dual carbon" goal,China is accelerating the pace of energy transformation,and the construction of a new power system is an important measure.On the one hand,the high proportion of new energy access systems poses a challenge to the balance of power supply and demand due to their strong output uncertainty.On the other hand,large-scale electric vehicles are rapidly developing into important loads within the system,and a large amount of disorderly charging resources entering the network will exacerbate the contradiction between supply and demand.Strengthening the guidance and management of electric vehicle load,optimizing and adjusting the distribution of electric vehicle load,is of strategic significance for ensuring the safe and stable operation of the system and improving resource utilization efficiency.Therefore,this article focuses on the issue of orderly charging guidance for a large number of electric vehicles,conducts in-depth research on the electricity demand and response characteristics of electric vehicle users,and achieves behavioral guidance for group users through the reasonable pricing strategy of load aggregators.Firstly,analyze the guidance model for orderly charging of electric vehicles.Conduct collaborative analysis on the participation of load aggregators in medium to long term,spot,and auxiliary service market trading mechanisms based on existing research;Sort out the main interaction relationship and price information transmission process between load aggregators,wholesale side power generators,and retail side users in the orderly charging guidance process of electric vehicles;Evaluate the guiding effect of orderly charging of electric vehicles from three aspects:reducing the deviation between supply and demand electricity,improving market transaction efficiency,and environmental benefits.Secondly,establish a response model for the group of electric vehicle users.Introducing the Huff model based on user decision-making behavior to predict individual user charging needs;Study the effects of factors such as travel time remaining,state of charge,and price changes on user charging response participation rate.By analyzing the tail correlation between the factors,select an appropriate Copula function to calculate the charging response participation rate under the combined effect of the influencing factors;On this basis,the bandwagon effect and response delay time of group users are analyzed,and their effect on user charging response is quantified,so as to establish a comprehensive response model of group users,which provides support for the price guidance of aggregate load.Once again,clarify the overall process of optimizing load aggregation pricing,and optimize the call for load aggregation based on the decomposition of medium and long term contracts and adjustable space for day-ahead transactions;The deviation curve between the generation side and the user side after load aggregation and optimization is used as the target curve for load aggregation pricing guidance;The peak and valley periods are modified,and combined with the response model of group users,a master-slave game model is established with the goal of maximizing the aggregator’s income and the user’s utility as the upper and lower levels respectively.The backward induction method is used to solve the game equilibrium price,so as to guide users to respond to the group target load.Finally,based on the data of load aggregators and electric vehicle users in Region A,simulation analysis is conducted to verify the effectiveness of the pricing optimization model established in this paper.The simulation results show that compared to the optimized aggregation scheme before optimization,the revised optimization pricing scheme during peak and valley periods increases the aggregator’s revenue by 63342.35 yuan,increases carbon emissions by 79.54 tons,and increases user response subsidies by 46850.24 yuan.This can improve the aggregator’s revenue and user utility while peak shaving and valley filling.This verifies that the aggregation pricing method proposed in this article is more effective and applicable for achieving physical,economic,and environmental goals,It can provide reference and support for guiding the orderly charging of group users,ensuring the safe and stable operation of the system,and promoting the construction of new power systems.