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Controlled Charging of Electric Vehicles to Minimize Energy Losses in Distribution Systems

机译:电动汽车的可控充电可最大程度地降低配电系统中的能量损失

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Abstract: Controlled electric vehicle (EV) charging scenarios are proposed, each characterized with an algorithm and associated computational and communication requirements, to be adopted by an EV aggregator or system operator. The proposed scenarios include uniform, random, conditional-random, and valley-filling charging scenarios. Different from previous studies, this paper focuses on easy-to-implement charging scenarios. Further, a modeling framework is presented to investigate the impact of the proposed charging scenarios on energy losses in distribution systems, as compared to an uncontrolled charging scenario and a reference scenario with no EVs. The modeling framework considers uncertainties involved in the behavior of low voltage customers and EV charging loads. It is applied to a distribution system for various case studies, including different penetrations and combinations of EVs with various characteristics. As seen by the results, although the valley-filling charging algorithm represents the optimal solution from the perspective of energy losses, the uniform charging scenario emerges as a quasi-optimal solution, having lower computational and communication requirements, which makes it easier to be adopted by EV aggregators or system operators. Further, with appropriately selected coefficients, the conditional-random charging algorithm can also exhibit a performance comparable to that of the uniform charging algorithm.
机译:摘要:提出了受控电动汽车(EV)充电方案,每种方案均具有算法以及相关的计算和通信要求,以供EV聚合商或系统运营商采用。拟议方案包括统一,随机,有条件随机和填谷方案。与以前的研究不同,本文重点介绍易于实现的计费方案。此外,与不受控制的充电方案和没有EV的参考方案相比,提出了一个建模框架来调查提议的充电方案对配电系统中能量损失的影响。建模框架考虑了低压客户行为和EV充电负载的不确定性。它适用于各种案例研究的配电系统,包括不同的电动汽车的渗透率和具有各种特性的组合。从结果可以看出,尽管从能量损失的角度来看,填谷式充电算法代表了最佳解决方案,但统一的充电方案却是准最优解决方案,具有较低的计算和通信要求,因此更易于采用由电动汽车聚合商或系统运营商提供。此外,利用适当选择的系数,条件随机充电算法也显示出比得上均匀充电算法的性能。

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