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Charging behavior characteristic simulation of plug-in electric vehicles for demand response

机译:需求响应的插电式电动汽车充电行为特性仿真

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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.
机译:本文旨在通过随机仿真获得插电式电动汽车(PEV)的自然充电行为特征(NCBC)。为此,提出了一种新颖的随机模拟方法。与早期的研究相比,该方法的优点是:1)不需要复杂的运输数据集; 2)在较长的时间范围(数周)内,更令人信服地模拟了聚合PEV的充电行为。然后,定义两个参数来表征大规模聚合PEV的自然充电行为。并利用所提出的仿真方法对这两个NCBC参数的时变模式进行了分析。最后,对大型异构PEV的NCBC参数结果进行了仿真。这些结果可用于评估总充电负载(ACL)的需求响应灵活性,这是设计智能充电方案的关键。

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