面向边缘智能的匹配充电桩式电动汽车有序充电方法OA

In response to the problems of insufficient consideration of charging pile resource constraints,low practicality of time-domain discrete models,and inadequate description of peak shaving capabilities in the current optimal scheduling of electric vehicles at charging stations,an optimal scheduling and peak shaving response capability evaluation method for electric vehicles oriented to edge intelligence was proposed based on the consideration of vehicle-pile matching.Firstly,an electric vehicle regulation and control architecture for charging stations oriented to edge intelligence was proposed.Secondly,time-domain continuous variables were used to represent the charging period,and a model of electric vehicle load and future available charging piles was constructed,with the introduction of a vehicle-pile matching matrix and constraints.Taking the guarantee of user charging demands as the primary goal and combining with the reduction of charging costs,an optimal scheduling model was established.Then,considering the translation constraints of electric vehicle loads under different peak shaving response capacities,a peak shaving response capability evaluation model was established.Finally,a typical scenario of an actual charging station was analyzed as an example,and the proposed method was compared with the traditional method that does not consider matching charging piles and time-domain discrete models to verify its effectiveness and practicality.