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Peer to Peer Energy Trading with Electric Vehicles

机译:电动汽车对等能源交易

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摘要

This paper presents a novel peer-to-peer energy trading system between two sets of electric vehicles, which significantly reduces the impact of the charging process on the power system during business hours. This trading system is also economically beneficial for all the users involved in the trading process. An activity-based model is used to predict the daily agenda and trips of a synthetic population for Flanders (Belgium). These drivers can be initially classified into three sets; after discarding the set of drivers who will be short of energy without charging chances due to their tight schedule, we focus on the two remaining relevant sets: those who complete all their daily trips with an excess of energy in their batteries and those who need to (and can) charge their vehicle during some daily stops within their scheduled trips. These last drivers have the chance to individually optimize their energy cost in the time-space dimensions, taking into account the grid electricity price and their mobility constraints. Then, collecting all the available offer/demand information among vehicles parked in the same area at the same time, an aggregator determines an optimal peer-to-peer price per area and per time slot, allowing customers with excess of energy in their batteries to share with benefits this good with other users who need to charge their vehicles during their daily trips. Results show that, when applying the proposed trading system, the energy cost paid by these drivers at a specific time slot and in a specific area can be reduced up to 71%.
机译:本文提出了一套新型的两套电动汽车之间的点对点能源交易系统,该系统显着减少了营业时间内充电过程对电力系统的影响。对于交易过程中涉及的所有用户,该交易系统在经济上也有利。基于活动的模型用于预测法兰德斯(比利时)的综合人口的日常日程和出行。这些驱动程序最初可以分为三组:在丢弃了因时间紧而缺少能量而又没有充电机会的那组驾驶员之后,我们将重点放在剩下的两个相关的组上:那些完成了所有日常出行且电池能量过剩的驾驶员和那些需要(并且可以)在预定行程中的某些日常停车期间为其车辆充电。考虑到电网电价及其移动性约束,这些最后的驱动程序有机会在时空维度上分别优化其能源成本。然后,汇总器会同时收集在同一区域内停放的所有车辆之间的所有可用报价/需求信息,聚合器确定每个区域和每个时段的最佳对等价格,从而使电池电量过剩的客户能够与需要在日常旅行中为车辆充电的其他用户共享这种好处。结果表明,在采用建议的交易系统时,这些驱动程序在特定时段和特定区域内支付的能源成本最多可降低71%。

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