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D2P: Distributed Dynamic Pricing Policyin Smart Grid for PHEVs Management

机译:D2P:智能电网中用于PHEV的分布式动态定价策略

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Future large-scale deployment of plug-in hybrid electric vehicles (PHEVs) will render massive energy demand on the electric grid during peak-hours. We propose an intelligent distributed dynamic pricing (D2P) mechanism for the charging of PHEVs in a smart grid architecture-an effort towards optimizing the energy consumption profile of PHEVs users. Each micro-grid decides realtime dynamic price as home-price and roaming-price, depending on the supply-demand curve, to optimize its revenue. Consequently, two types of energy services are considered-home micro-grid energy, and foreign micro-grid energy. After designing the PHEVs' mobility and battery models, the pricing policies for the home-price and the roaming-price are presented. A decision making process to implement a cost-effective charging and discharging method for PHEVs is also demonstrated based on the real-time price decided by the micro-grids. We evaluate and compare the results of distributed pricing policy with other existing centralized/distributed ones. Simulation results show that using the proposed architecture, the utility corresponding to the PHEVs increases by approximately 34 percent over that of the existing ones for optimal charging of PHEVs.
机译:插电式混合动力汽车(PHEV)的未来大规模部署将在高峰时段为电网带来巨大的能源需求。我们提出了一种智能分布式动态定价(D2P)机制,用于在智能电网架构中为PHEV充电-努力优化PHEV用户的能耗分布。每个微电网根据供求曲线将实时动态价格确定为房屋价格和漫游价格,以优化其收入。因此,两种能源服务被认为是家用微电网能源和国外微电网能源。在设计了插电式混合动力汽车的机动性和电池模型之后,提出了房屋价格和漫游价格的定价政策。基于微电网确定的实时价格,还演示了为PHEV实施具有成本效益的充电和放电方法的决策过程。我们评估并比较了分布式定价策略与其他现有集中式/分布式策略的结果。仿真结果表明,使用所提出的体系结构,与PHEV对应的实用程序比现有的PHEV实用程序增加了约34%,以实现PHEV的最佳充电。

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