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A novel software defined wireless sensor network based grid to vehicle load management system

机译:一种基于软件的新型无线传感器网络网格到车辆负荷管理系统

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This paper proposes a novel software defined wireless sensor network (SDWSN) based grid to vehicle (G2V) load management scheme to initiate off peak hour valley filling of the daily power supply curve. In particular, this paper focuses on domestic Plug-in Electric Vehicles (PEVs) charging that adopts smart energy allocation technique to maximize the number of charging vehicles and uses a Software Defined Network (SDN) to enable adaptive energy supply. A novel energy scheduling algorithm is proposed based on a linear prediction algorithm that suits the network model built upon a SDN paradigm. To demonstrate the proof of concept, an SDN based Smart Grid Neighborhood Area network (SGNAN) operating onto Wireless Sensor Network (WSN) is developed using Castalia. Simulation results show that the proposed SDWSN network architecture can efficiently support the G2V load management scheme and enables smart valley filling of the daily load curve for maximum utilization of power generation capacity.
机译:本文提出了一种新颖的基于软件定义的无线传感器网络(SDWSN)的网格到车辆(G2V)负载管理方案,以启动非高峰时段的每日电源曲线填充。特别是,本文重点介绍了采用智能能源分配技术以最大化充电车辆数量并使用软件定义网络(SDN)来实现自适应能源供应的家用插电式电动汽车(PEV)充电。提出了一种新的基于线性预测算法的能量调度算法,该算法适合于基于SDN范式的网络模型。为了演示概念验证,使用Castalia开发了基于SDN的,运行于无线传感器网络(WSN)上的基于SDN的智能电网邻域网(SGNAN)。仿真结果表明,所提出的SDWSN网络架构可以有效地支持G2V负载管理方案,并且可以智能填充每日负载曲线,从而最大程度地利用发电容量。

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