Research On Optimizing Allocation Method Of Electric Vehicle Charging Resources Based On Information Interaction

Nowadays,energy and environmental crisis have become increasingly serious,electric vehicles(EVs)have attracted wide attention over the world due to their lowcarbon and environmental friendly characteristics.With the development of smart grid,the penetration rate of EVs will also grow rapidly.Large-scale EVs connected to the grid will bring significant impact on power system.To design intelligent charging strategies for EVs,and to realize the optimal allocation of power resources have become a research hotspot in the field of energy Internet.This thesis analyzes the research status of smart grid technology and intelligent charging strategies for EVs,then studies the impact largescale EVs bring on the power grid.The communication technologies and their applications involving two-way interaction between EVs and smart grid are discussed.A scheme of EVs charging information interactive platform is put forwarded.On this basis,the thesis takes household EVs charging in residential areas as the main research object.The existing problems are analyzed and their solutions are discussed.In order to optimize the charging resource allocation,intelligent EVs charge control strategies based on information interaction are proposed in this thesis.In order to secure electrical safety and satisfy various needs of electric vehicle users,a load allocation strategy for electric vehicle charging is put forward.Considering the constraints of distribution network,battery situation,users' waiting time and charging demands,a dynamic coordination allocation algorithm based on demand priority is proposed.The results show the effectiveness of the proposed scheme,which could dynamically adjust the charging rate of the electric vehicles according to the load level of common transformer area.This method will improve the level of customer satisfaction without violation of grid constraints,it's applicable to common transformer area with limited power supply.Another aim is to reduce the burden on the power grid and to balance power resource utilization.This thesis proposed a random access electric vehicle charging control strategy based on autonomous decision making.The control decision generator obtains electricity price and load information of current control area,then divide valley period into several parts.Each part's load capacity is calculated by control decision generator.According to the load capacity,control decision generator calculates different charging duration of the user's charging start time probability distribution through the method mentioned in this article.Each charging pile randomly determines start charging time based on probability distribution.The proposed method quantifies the load capacity of the grid during the valley period as probability distribution.The charging task is generated randomly according to the load capacity of each period.As a result,the utilization of valley power resources is balanced.Without complicated centralized communication control,the charging task is independently decided by the charging pile.The effectiveness of such strategy is tested with Monte Carlo method.Results show that the proposed strategy can effectively realize peak load shifting and stabilize the load fluctuation,the system and user costs are also reduced.