Charging Behavior Characteristic Simulation of Plug-in Electric Vehicles for Demand Response

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    This paper aims to obtain the natural charging behavior characteristic (NCBC) of plug-in electric vehicles (PEVs) via stochastic simulation. To this end, a novel stochastic simulating methodology is proposed. Compared to earlier studies, advantages of the proposed methodology are: 1) it does not need sophisticated transportation datasets; 2) it simulates the charging behaviors of aggregated PEVs more convincingly for a long time window (multi weeks). Then, two parameters are defined to characterize the natural charging behaviors of the large scale aggregated PEVs. And the time-varying pattern of these two NCBC-parameters are analyzed by using the proposed simulating methodology. Finally, the results of NCBC-parameters for large scale heterogeneous PEVs are simulated. These results can be used to evaluate the demand response flexibility of the aggregated charging load (ACL), which is the key to design smart charging schemes.

 

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