With the increasing number of electric vehicles(EVs),EV charging significantly increases the total load of the commu-nity,greatly increases the carbon emissions of the community,brings great instability to the community power grid,and reduces the power quality of the community.This paper studies the problem of scheduling EV charging based on the constraints of carbon peak when the arrival time,departure time,and charging demand of EVs are not known in advance.First,we formulate and study the problem of charging EVs without knowing future information.Aiming to address the uncertainty of EV charging behavior,we propose an algorithm for intelligent charging carbon emissions using the actor-critic approach,which learns the optimal strategy for EV charging through continuous charging instead of using a discrete approximation of carbon emissions.Simulation results demonstrate that compared with the online charging algorithm and the AEM energy management algorithm,the proposed algo-rithm can reduce the expected cost by 24.03％and 21.49％.
维普
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