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Mobility-Aware Vehicle-to-Grid (V2G) Optimization for Uniform Utilization in Smart Grid Based Power Distribution Network

机译:基于智能电网的配电网络中用于统一利用的移动感知车对网(V2G)优化

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One of the critical bottlenecks of high penetration of Electric Vehicles (EV) is uncoordinated, simultaneous charging of many EVs that can potentially impact the electric distribution grid with unwanted peak load demand. V2G technology enables the bidirectional flow of electric energy where EVs can also discharge energy to the grid from their batteries aiming to lower the peak demand. Our V2G optimization approach employs mobility information to balance peak utilization among differently utilized distribution segments by assigning each EV to an optimal Electric Vehicle Supply Equipment (EVSE) enabled parking lot. By aggregating geographically dispersed EVs and micro-grids with renewable energy sources as a virtual power plant (VPP), we proposed a scalable VPP based V2G optimization architecture integrated with VANET. Compared with existing solutions, our convex optimization algorithm uses fewer variables, attains uniform utilization of grid nodes by optimal EV charging/discharging profiles. By simulation, we showed that this novel mobility-aware, scalable V2G optimization algorithm can reduce or significantly postpone the need of expensive upgrade of power distribution infrastructure.
机译:电动汽车(EV)的高普及率的关键瓶颈之一是不协调,同时为许多EV充电,这可能会给电网带来不必要的峰值负载需求。 V2G技术使电能能够双向流动,而电动汽车也可以从电池向电网释放能量,以降低峰值需求。我们的V2G优化方法利用移动性信息,通过将每个EV分配给具有最佳电动车辆供应设备(EVSE)功能的停车场,来平衡不同利用的分配段之间的峰值利用率。通过将分散在地理位置上的电动汽车和微电网与可再生能源作为虚拟电厂(VPP)进行汇总,我们提出了与VANET集成的基于可伸缩VPP的V2G优化架构。与现有解决方案相比,我们的凸优化算法使用的变量更少,并通过最佳EV充电/放电曲线实现了网格节点的统一利用。通过仿真,我们表明,这种新颖的可感知移动性的可扩展V2G优化算法可以减少或显着推迟对配电基础架构进行昂贵升级的需求。

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