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

机译:用于需求响应的插入电动车辆的充电行为特征模拟

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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入电动车辆(PEV)的自然充电行为特征(NCBC)。为此,提出了一种新型随机模拟方法。与早期的研究相比,所提出的方法的优点是:1)它不需要复杂的交通数据集; 2)它更令人信服地模拟聚合PEV的充电行为,长时间窗口(多周数)。然后,定义了两个参数以表征大规模聚合PEV的自然充电行为。通过使用所提出的模拟方法来分析这两个NCBC参数的时变模式。最后,模拟了大规模异构PEV的NCBC参数的结果。这些结果可用于评估聚合充电负荷(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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