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Electric vehicle capacity forecasting model with application to load levelling

机译:电动车辆容量预测模型应用于载荷调平

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There are many uncertainties associated with forecasting electric vehicle charging and discharging capacity due to the stochastic nature of human behavior surrounding usage and intermittent travel patterns. This uncertainty if unmanaged has the potential to radically change traditional load profiles. Therefore optimal capacity forecasting methods are important for large-scale electric vehicle integration in future power systems. This paper develops a capacity forecasting model considering eight particular uncertainties under three categories to overcome this issue. The model is then applied to a UK summer scenario in 2020. The results of this analysis demonstrate that the proposed model is accurate for charge and discharge prediction and a feasible basis for steady-state analysis required for large-scale electric vehicle integration.
机译:由于人类行为周围的使用和间歇性旅行模式,存在与预测电动车辆充电和放电容量有许多不确定性。如果非托管有可能从根本上改变传统的负载型材,这种不确定性。因此,最佳的容量预测方法对于未来电力系统的大型电动车集成是重要的。本文开发了考虑在三个类别下的八个特别的不确定性来克服这一问题的容量预测模型。然后将该模型应用于2020年的英国夏季情景。该分析的结果表明,该模型准确地用于充电和放电预测和大型电动车辆集成所需的稳态分析的可行基础。

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