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Optimal EV charging and discharging control considering dynamic pricing

机译:考虑动态定价的最优EV充放电控制

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EV penetration allows the bidirectional power flow between power grid and EV, called vehicle-to-grid (V2G). The V2G implementation requires different price signals, such as real-time pricing (RTP) and time-of-use pricing (TOU). This work investigates the smart EVs charging control problem at a distribution transformer level. In order to evaluate the peak shaving and the transformer load factor increasing due to coordinated V2G process, three EV penetration levels are evaluated: 30%, 60% and 100% of residential households with one EV. The charging and discharging of the battery is optimized to minimize the net electricity cost during a 24-hour period, with three different types of dynamic prices. The computational model was developed using the Matlab/Simulink and a linear programming technique is used. The results shows that coordinated charging control limits the peak demand elevation and provide peak shaving for substation and distribution transformers. The instantaneous RTP showed better results and TOU could shift the demand peak to another time of the day.
机译:EV渗透允许在电网和EV之间进行双向功率流动,称为车辆到电网(V2G)。 V2G的实现需要不同的价格信号,例如实时定价(RTP)和使用时间定价(TOU)。这项工作研究了配电变压器一级的智能电动汽车充电控制问题。为了评估由于V2G协调处理而导致的峰值削波和变压器负载因子的增加,评估了三种EV渗透水平:拥有EV的30%,60%和100%的居民家庭。通过三种不同类型的动态价格,对电池的充电和放电进行了优化,以最大程度地降低24小时内的净电力成本。使用Matlab / Simulink开发了计算模型,并使用了线性编程技术。结果表明,协调的充电控制限制了峰值需求的上升,并为变电站和配电变压器提供了削峰。即时RTP显示出更好的结果,并且TOU可以将需求高峰转移到一天中的其他时间。

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