Energy Management for EV Charging in Software-Defined Green Vehicle-to-Grid Network

Vehicle-to-grid (V2G) networks are expected to balance the supply and demand in smart grid by reducing the peak-to-average ratio of power grid load curve. We are entering the era of wireless communication, where we can enjoy various advantages such as lower cost, lower battery consumption, and lower access latency. We believe advanced wireless communication techniques have great potential to further promote the economical deployment of V2G network and lower energy consumption. In this article, we address the green V2G network for efficient energy management. However, we still face many challenging issues even if we exploit the promising wireless communication technique in green V2G networks. For example, it becomes more and more challenging to achieve the efficiency and economy of renewable energy resource allocation due to the increasing number of electric vehicles and limited capacity of local aggregators (LAGs). To address the issues, we consider a software-defined green V2G network for energy management, which consists of three planes: management plane, control plane, and data plane. Specifically, the control plane is aimed at guiding both data flow and energy flow to implement an efficient and economic strategy for energy scheduling, while the data plane collects the information through LAGs for the customized services in the management plane. Additionally, we present an energy management scheme of charging stations as a case study. Simulation results reveal that our proposals could achieve delightful performance on global optimization in the software-defined green V2G network.车网互动（Vehicle-to-Grid, V2G）网络有望通过降低电网负荷曲线的峰均比，实现智能电网的供需平衡。我们正步入无线通信时代，可尽享低成本、低电池功耗、低接入时延等诸多优势。我们认为，先进的无线通信技术具备极大潜力，可进一步推动车网互动网络的经济性部署并降低能源消耗。本文针对面向高效能源管理的绿色车网互动网络展开研究。然而，即便在绿色车网互动网络中应用前景广阔的无线通信技术，我们仍面临诸多挑战性难题。例如，随着电动汽车数量不断增加，且本地聚合器（Local Aggregators, LAGs）的容量有限，实现可再生能源分配的高效性与经济性正变得愈发困难。为解决上述问题，本文提出一种面向能源管理的软件定义绿色车网互动网络，该网络包含三大平面：管理平面（Management Plane）、控制平面（Control Plane）与数据平面（Data Plane）。具体而言，控制平面负责引导数据流与能源流，以制定高效经济的能源调度策略；数据平面则通过本地聚合器（LAGs）采集相关信息，为管理平面的定制化服务提供数据支撑。此外，本文以充电站为研究场景，提出一种能源管理方案并展开案例分析。仿真结果表明，所提方案可在软件定义绿色车网互动网络中实现出色的全局优化性能。