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A Linear Programming Methodology to Quantify the Impact of PHEVs with V2G Capabilities on Distribution Systems

机译:用于量化具有V2G功能的插电式混合动力汽车对配电系统的影响的线性规划方法

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The Smart Grid Initiative (SGI) encourages the integration of storage and peak-shaving technologies including plug-in hybrid electric vehicles (PHEVs). PHEV sales in the US are expected to significantly increase primarily due to their potential to lower fuel costs by reducing fossil fuel consumption and to lower emissions. The rising penetration rate of these vehicles may however cause problems to utilities, especially as they may dramatically increase demand peaks if not managed properly. In this paper, a methodology is proposed to determine the impact of PHEV fleets with vehicle-to-grid (V2G) capabilities on electric distribution systems. The methodology relies on a probabilistic PHEV fleet characteristics model and a linear programming algorithm to determine the optimal charging patterns of the fleet vehicles, which are then used for utility peak-shaving purposes. Results for several scenarios show that a 30% penetration level of V2G-capable PHEVs can be achieved without increasing peak load and without requiring any capacity update on the distribution infrastructure of the selected test system. Detailed results also show that daily load profiles would be modified for residential customers, and would stay closer to their average value than today.
机译:智能电网计划(SGI)鼓励集成存储和调峰技术,包括插电式混合动力汽车(PHEV)。预计PHEV在美国的销量将显着增长,这主要是因为它们有可能通过减少化石燃料的消耗和减少排放来降低燃料成本。但是,这些车辆普及率的上升可能给公用事业带来麻烦,尤其是如果管理不当,它们可能会大大增加需求高峰。在本文中,提出了一种方法来确定具有车对网(V2G)功能的PHEV车队对配电系统的影响。该方法依赖于概率PHEV车队特征模型和线性规划算法来确定车队车辆的最佳充电模式,然后将其用于公用事业削峰目的。几种方案的结果表明,在不增加峰值负载且无需对所选测试系统的分布基础设施进行任何容量更新的情况下,可以实现30%的支持V2G的PHEV渗透率。详细的结果还显示,住宅用户的每日负荷曲线将被修改,并且将保持在比今天更接近其平均值的水平。

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