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Priority-based vehicle-to-grid scheduling for minimization of power grid load variance

机译:基于优先的车辆到网格调度,用于最小化电网负载方差

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Electric vehicles are considered as additional loads to the power grid and may pose possible threats to the power grid reliability by overloading the grid equipment, disturbing the grid voltage stability and injecting harmonics into the power grid. Nonetheless, electric vehicles can also provide supports to the power grid through Vehicleto-Grid application by discharging battery energy into the power grid. This paper presents an optimal priority-based Vehicle-to-Grid scheduling with the objective to minimize the grid load variance. An optimal strategy was developed to optimize the amount of charging/discharging power based on the electric vehicle battery's state-of-charge. This study desires to find a central point which can benefit power utility and electric vehicle users. The algorithm can operate in three modes, which are valley filling, peak load shaving and priority charging. The charging of the electric vehicle can be performed in all three modes, as long as the charging of electric vehicle is required. Meanwhile, discharging of the electric vehicle only occurs during peak load shaving mode. To ensure the practicability of this study, numerous constraints were considered and the study was conducted in a commercial-residential area with electric vehicle mobility of 1300. The results indicated that the algorithm was able to minimize the grid load variance while prioritizing the electric vehicle with a low percentage of state-of-charge. The original maximum variation between peak loading and off-peak loading measured at 5 MW was effectively reduced to 1.5 MW following the deployment of the proposed algorithm.
机译:电动车辆被认为是电网的额外负载,并且可以通过将电网设备重载,使电网电压稳定性和注入谐波注入电网来构成电网可靠性的可能威胁。尽管如此,通过将电池能量放入电网,电动车辆还可以通过车辆电网应用提供对电网的支持。本文介绍了基于优先的基于车辆到网格调度,目的是最小化电网负载方差。开发了一种最佳策略,以优化基于电动车辆电池的充电量的充电/放电功率。本研究希望找到一种能够效益电力电力和电动汽车用户的中心点。该算法可以采用三种模式操作,这是谷填充,峰值负荷剃须和优先收费。只要需要电动车辆的充电即可,可以在所有三种模式中执行电动车辆的充电。同时,在峰值负荷剃须模式期间仅发生电动车辆的放电。为了确保本研究的实用性,考虑了许多限制,并在商业住宅区进行了电动汽车移动性的研究。结果表明该算法能够最小化电流载荷方差,同时利用电动汽车低百分比的充电。在算法部署后,在5 MW下测量的峰值加载和截止峰值加载之间的最大变化有效地降低到1.5 MW。

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