Considering the stochastic charging behaviors of electric vehicles(EVs)

a software simulation is conducted to simulate the driving patterns of users. Based on the virtual battery aggregation model

a novel double-layer charging control strategy for EV is developed. By synthesizing the strength of the two mainstream control strategies

i. e. centralized control strategy and decentralized control strategy

the charging control is divided into two levels with different optimal objectives. For the upper control layer

the global interests are taken into consideration

and peak load

node voltage and overall electricity cost are adopted as the global optimal objectives. For the bottom layer

in order to consider the high penetrations of EVs

the scalable and flexible alternating direction method of multipliers(ADMM)algorithm is deployed

which blends the benefits of dual decomposition and augmented Lagrangian methods to solve the optimal problem. To verify the effectiveness of the proposed method

four scenarios are simulated and their effects on node voltage

line load

and daily load curve are compared and analyzed. The results indicate that under the proposed charging control strategy

higher node voltage

lower line load and smoother load curve can be achieved.