Orderly Charging Scheduling Strategy Of Electric Vehicles Considering User Behavior

With the vigorous promotion of the construction of new power systems,distributed new energy represented by wind and solar power is developing rapidly and due to its characteristics of on-site development and consumption,flexible demand-side resources are required to support consumption.At the same time,with the large-scale construction of charging facilities,it provides a bridge for the coordination and matching of electric vehicles and distributed new energy.By formulating guiding strategies,the charging behavior of electric vehicles can be guided.When distributed new energy is abundant in output,it is guided to charge and consume,and when the output of distributed new energy is insufficient,the charging load is reduced or transferred to reduce the impact of electric vehicles and distributed new energy on the power system.Therefore,this article proposes an orderly charging scheduling strategy for electric vehicles considering user behavior for a single charging station and multiple charging areas.For the scenario of a single charging station,the competitive pricing incentive strategy of a single charging station is proposed by taking full account of the competitive relations among charging stations,integrating the traffic road information and the charging decision-making behavior of EV users.In terms of the charging demand model of EV users,considering their impatience when queuing up at charging stations and their behavior characteristics of refusing to take in due to too long queue,a revised charging demand model considering user queuing behavior was proposed.Finally,the simulation verifies that the strategy in this paper can improve the economic benefits of charging stations,promote the consumption of distributed new energy,and improve user satisfaction.Based on the distributed new energy output of each region and the matching situation of EV charging load,the multi-region scheduling strategy of EV is proposed for the multi-charging region scenario.In this paper,EV user time anxiety model is constructed in view of the lack of expected charging time of travel users,and EV user charging demand model is constructed based on user time anxiety and price elasticity of demand.According to the differentiated response characteristics of electric vehicles,a charging area decision model based on regret theory was proposed for the responsive cluster.Finally,the simulation and comparison experiments prove the advantages of the proposed strategy in improving the economic benefits of charging stations,reducing the consumption deviation of distributed new energy,and reducing users’ charging costs.