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Fuzzy logic-based charging strategy for electric vehicles plugged into a smart grid

机译:基于模糊的基于逻辑的电动车充电策略插入智能电网

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摘要

The smart grid allows its consumers to participate in producing cost effective, sustainable, and environmentally friendly electricity. The consumers in a smart grid, for example, can plug their electric vehicles (EVs) into the grid to charge and discharge their vehicles' batteries. However, charging of the electric vehicles, especially during the peak periods, can adversely impact the grid performance. Thus, in this paper, the coordinated charging of the electric vehicles problem is tackled. A fuzzy logic-based approach is developed to coordinate the electric vehicle charging such that the system minimum voltage is within the allowable limits. The inputs to the fuzzy charging controller (FCC) include the states of charge (SOC) of the electric vehicles and the grid parameters represented in the system minimum voltage. The output of the FCC is the charging levels of the electric vehicles' batteries. The developed fuzzy logic-based charging strategy was validated on the 69-bus test system. The fuzzy charging (FC) was compared with three modes of uncoordinated charging, namely slow charging (SC), medium charging (MC), and fast charging (FC). The results of the comparative study prove the superiority of the developed fuzzy charging approach over uncoordinated charging schemes.
机译:智能电网允许其消费者参与生产成本效益,可持续和环保的电力。例如,智能电网中的消费者可以将其电动车辆(EVS)插入电网,以充电和排出其车辆的电池。然而,电动车辆的充电,特别是在高峰期期间,可能对网格性能产生不利影响。因此,在本文中,解决了电动车辆问题的协调充电。开发了一种模糊的基于逻辑的方法以协调电动车辆充电,使得系统最小电压在允许的限度内。对模糊充电控制器(FCC)的输入包括电动车辆的电荷(SoC)和在系统最小电压中表示的网格参数。 FCC的输出是电动汽车电池的充电水平。在69总线测试系统上验证了发达的模糊逻辑的充电策略。将模糊充电(FC)与三种不协调的充电模式进行了比较,即缓慢充电(SC),介质充电(MC)和快速充电(FC)。比较研究的结果证明了超出了不协调的充电方案的发达模糊充电方法的优越性。

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